
@inproceedings{yang_l2_2011,
	address = {Barcelona, Catalonia, Spain},
	series = {{IJCAI}'11},
	title = {L2,1-norm {Regularized} {Discriminative} {Feature} {Selection} for {Unsupervised} {Learning}},
	booktitle = {Proceedings of the {Twenty}-{Second} {International} {Joint} {Conference} on {Artificial} {Intelligence} - {Volume} {Volume} {Two}},
	publisher = {AAAI Press},
	author = {Yang, Yi and Shen, Heng Tao and Ma, Zhigang and Huang, Zi and Zhou, Xiaofang},
	year = {2011},
	pages = {1589--1594}
}

@article{zhu_nonconvex_2017,
	title = {Non-convex regularized self-representation for unsupervised feature selection},
	volume = {60},
	journal = {Image and Vision Computing},
	author = {Zhu, Pengfei and Zhu, Wencheng and Wang, Weizhi and Zuo, Wangmeng and Hu, Qinghua},
	month = apr,
	year = {2017},
	pages = {22--29}
}

@article{zhu_unsupervised_2015,
	title = {Unsupervised feature selection by regularized self-representation},
	volume = {48},
	number = {2},
	journal = {Pattern Recognition},
	author = {Zhu, Pengfei and Zuo, Wangmeng and Zhang, Lei and Hu, Qinghua and Shiu, Simon C.K.},
	month = feb,
	year = {2015},
	pages = {438--446}
}

@article{liu_unsupervised_2017,
	title = {Unsupervised feature selection via {Diversity}-induced {Self}-representation},
	volume = {219},
	journal = {Neurocomputing},
	author = {Liu, Yanbei and Liu, Kaihua and Zhang, Changqing and Wang, Jing and Wang, Xiao},
	month = jan,
	year = {2017},
	pages = {350--363}
}

@article{fang_locality_2014,
	title = {Locality and similarity preserving embedding for feature selection},
	volume = {128},
	journal = {Neurocomputing},
	author = {Fang, Xiaozhao and Xu, Yong and Li, Xuelong and Fan, Zizhu and Liu, Hong and Chen, Yan},
	month = mar,
	year = {2014},
	pages = {304--315}
}

@article{lu_structure_2018,
	title = {Structure preserving unsupervised feature selection},
	volume = {301},
	journal = {Neurocomputing},
	author = {Lu, Quanmao and Li, Xuelong and Dong, Yongsheng},
	month = aug,
	year = {2018},
	pages = {36--45},
	file = {[Lu.2018] Structure preserving unsupervised feature selection.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Lu.2018] Structure preserving unsupervised feature selection.pdf:application/pdf}
}

@article{bair_prediction_2006,
	title = {Prediction by {Supervised} {Principal} {Components}},
	volume = {101},
	number = {473},
	journal = {Journal of the American Statistical Association},
	author = {Bair, Eric and Hastie, Trevor and Paul, Debashis and Tibshirani, Robert},
	month = mar,
	year = {2006},
	pages = {119--137}
}

@article{liu_local_2016,
	title = {Local linear {Laplacian} eigenmaps: {A} direct extension of {LLE}},
	volume = {75},
	journal = {Pattern Recognition Letters},
	author = {Liu, Feng and Zhang, Weijie and Gu, Suicheng},
	month = may,
	year = {2016},
	pages = {30--35},
	file = {[Liu.2016] Local linear Laplacian eigenmaps.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Liu.2016] Local linear Laplacian eigenmaps.pdf:application/pdf}
}

@inproceedings{kegl_intrinsic_2002,
	address = {Cambridge, MA, USA},
	series = {{NIPS}'02},
	title = {Intrinsic {Dimension} {Estimation} {Using} {Packing} {Numbers}},
	booktitle = {Proceedings of the 15th {International} {Conference} on {Neural} {Information} {Processing} {Systems}},
	publisher = {MIT Press},
	author = {Kégl, Balázs},
	year = {2002},
	pages = {697--704}
}

@inproceedings{eriksson_estimating_2012,
	address = {Ann Arbor, MI, USA},
	title = {Estimating intrinsic dimension via clustering},
	booktitle = {2012 {IEEE} {Statistical} {Signal} {Processing} {Workshop} ({SSP})},
	publisher = {IEEE},
	author = {Eriksson, Brian and Crovella, Mark},
	month = aug,
	year = {2012},
	pages = {760--763}
}

@inproceedings{farahmand_manifoldadaptive_2007,
	series = {{ACM} {International} {Conference} {Proceeding} {Series}},
	title = {Manifold-adaptive dimension estimation},
	volume = {227},
	booktitle = {{ICML}},
	publisher = {ACM},
	author = {Farahmand, Amir Massoud and Szepesvári, Csaba and Audibert, Jean-Yves},
	year = {2007},
	pages = {265--272}
}

@inproceedings{hein_intrinsic_2005,
	title = {Intrinsic dimensionality estimation of submanifolds in {R} $^{\textrm{d}}$\$},
	booktitle = {Proceedings of the 22nd international conference on {Machine} learning},
	publisher = {ACM Press},
	author = {Hein, Matthias and Audibert, Jean-Yves},
	year = {2005},
	pages = {289--296}
}

@article{facco_estimating_2017,
	title = {Estimating the intrinsic dimension of datasets by a minimal neighborhood information},
	volume = {7},
	number = {1},
	journal = {Scientific Reports},
	author = {Facco, Elena and d’Errico, Maria and Rodriguez, Alex and Laio, Alessandro},
	month = dec,
	year = {2017}
}

@article{aflalo_spectral_2013,
	title = {Spectral multidimensional scaling},
	volume = {110},
	number = {45},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Aflalo, Y. and Kimmel, R.},
	month = nov,
	year = {2013},
	pages = {18052--18057}
}

@misc{mackay_comments_2005,
	title = {Comments on '{Maximum} {Likelihood} {Estimation} of {Intrinsic} {Dimension}' by {E}. {Levina} and {P}. {Bickel} (2004)},
	url = {http://www.inference.org.uk/mackay/dimension/},
	author = {MacKay, D.J.C. and Ghahramani, Zoubin},
	month = jan,
	year = {2005}
}

@incollection{levina_maximum_2005,
	title = {Maximum {Likelihood} {Estimation} of {Intrinsic} {Dimension}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 17},
	publisher = {MIT Press},
	author = {Levina, Elizaveta and Bickel, Peter J.},
	editor = {Saul, L. K. and Weiss, Y. and Bottou, L.},
	year = {2005},
	pages = {777--784}
}

@article{pettis_intrinsic_1979,
	title = {An {Intrinsic} {Dimensionality} {Estimator} from {Near}-{Neighbor} {Information}},
	volume = {PAMI-1},
	number = {1},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	author = {Pettis, Karl W. and Bailey, Thomas A. and Jain, Anil K. and Dubes, Richard C.},
	month = jan,
	year = {1979},
	pages = {25--37}
}

@article{verveer_evaluation_1995,
	title = {An evaluation of intrinsic dimensionality estimators},
	volume = {17},
	number = {1},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	author = {Verveer, P.J. and Duin, R.P.W.},
	month = jan,
	year = {1995},
	pages = {81--86}
}

@article{fan_intrinsic_2009,
	title = {Intrinsic dimension estimation of manifolds by incising balls},
	volume = {42},
	number = {5},
	journal = {Pattern Recognition},
	author = {Fan, Mingyu and Qiao, Hong and Zhang, Bo},
	month = may,
	year = {2009},
	pages = {780--787}
}

@inproceedings{minghim_contentbased_2006,
	address = {San Jose, CA},
	title = {Content-based text mapping using multi-dimensional projections for exploration of document collections},
	booktitle = {Visualization and {Data} {Analysis}},
	author = {Minghim, Rosane and Paulovich, Fernando V. and de Andrade Lopes, Alneu},
	editor = {Erbacher, Robert F. and Roberts, Jonathan C. and Gröhn, Matti T. and Börner, Katy},
	month = jan,
	year = {2006},
	pages = {60600S}
}

@article{tejada_improved_2003,
	title = {On {Improved} {Projection} {Techniques} to {Support} {Visual} {Exploration} of {Multidimensional} {Data} {Sets}},
	volume = {2},
	number = {4},
	journal = {Information Visualization},
	author = {Tejada, Eduardo and Minghim, Rosane and Nonato, Luis Gustavo},
	month = dec,
	year = {2003},
	keywords = {dimensionality reduction, fastmap, force scheme, NNP, projection error estimation, projection-based visualization techniques},
	pages = {218--231}
}

@article{joia_local_2011,
	title = {Local {Affine} {Multidimensional} {Projection}},
	volume = {17},
	number = {12},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	author = {Joia, P. and Paulovich, Fernando V. and Coimbra, Danilo and Cuminato, Jose Alberto and Nonato, Luis Gustavo},
	month = dec,
	year = {2011},
	pages = {2563--2571},
	file = {[Joia.2011] Local Affine Multidimensional Projection.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Joia.2011] Local Affine Multidimensional Projection.pdf:application/pdf}
}

@inproceedings{faloutsos_fastmap_1995,
	address = {San Jose, California, United States},
	title = {{FastMap}: a fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets},
	booktitle = {Proceedings of the 1995 {ACM} {SIGMOD} international conference on {Management} of data - {SIGMOD} '95},
	publisher = {ACM Press},
	author = {Faloutsos, Christos and Lin, King-Ip},
	year = {1995},
	pages = {163--174}
}

@article{paulovich_piece_2011,
	title = {Piece wise {Laplacian}-based {Projection} for {Interactive} {Data} {Exploration} and {Organization}},
	volume = {30},
	number = {3},
	journal = {Computer Graphics Forum},
	author = {Paulovich, F.V. and Eler, D.M. and Poco, J. and Botha, C.P. and Minghim, R. and Nonato, L.G.},
	month = jun,
	year = {2011},
	pages = {1091--1100},
	file = {[Paulovich.2011] Piece wise Laplacian-based Projection for Interactive Data Exploration and.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Paulovich.2011] Piece wise Laplacian-based Projection for Interactive Data Exploration and.pdf:application/pdf}
}

@inproceedings{nadler_diffusion_2005,
	address = {Cambridge, MA, USA},
	series = {{NIPS}'05},
	title = {Diffusion {Maps}, {Spectral} {Clustering} and {Eigenfunctions} of {Fokker}-{Planck} {Operators}},
	booktitle = {Proceedings of the 18th {International} {Conference} on {Neural} {Information} {Processing} {Systems}},
	publisher = {MIT Press},
	author = {Nadler, Boaz and Lafon, Stéphane and Coifman, Ronald R. and Kevrekidis, Ioannis G.},
	year = {2005},
	keywords = {algorithms and architectures, learning theory},
	pages = {955--962}
}

@inproceedings{porte_introduction_2008,
	title = {An introduction to diffusion maps},
	booktitle = {In {The} 19th {Symposium} of the {Pattern} {Recognition} {Association} of {South} {Africa}},
	author = {Porte, J. De La and Herbst, B. M. and Hereman, W. and Walt, S. J. Van Der},
	year = {2008},
	file = {[Porte.2008] An introduction to diffusion maps.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Porte.2008] An introduction to diffusion maps.pdf:application/pdf}
}

@article{achlioptas_databasefriendly_2003,
	title = {Database-friendly random projections: {Johnson}-{Lindenstrauss} with binary coins},
	volume = {66},
	number = {4},
	journal = {Journal of Computer and System Sciences},
	author = {Achlioptas, Dimitris},
	month = jun,
	year = {2003},
	pages = {671--687}
}

@article{pearson_liii_1901,
	title = {{LIII}. {On} lines and planes of closest fit to systems of points in space},
	volume = {2},
	number = {11},
	journal = {Philosophical Magazine Series 6},
	author = {Pearson, Karl},
	month = nov,
	year = {1901},
	pages = {559--572},
	file = {[Pearson.1901] LIII.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Pearson.1901] LIII.pdf:application/pdf}
}

@article{zhang_principal_2004,
	title = {Principal {Manifolds} and {Nonlinear} {Dimensionality} {Reduction} via {Tangent} {Space} {Alignment}},
	volume = {26},
	number = {1},
	journal = {SIAM Journal on Scientific Computing},
	author = {Zhang, Zhenyue and Zha, Hongyuan},
	month = jan,
	year = {2004},
	pages = {313--338},
	file = {[Zhang.2004] Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhang.2004] Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space.pdf:application/pdf}
}

@article{zhang_linear_2007,
	title = {Linear local tangent space alignment and application to face recognition},
	volume = {70},
	number = {7-9},
	journal = {Neurocomputing},
	author = {Zhang, Tianhao and Yang, Jie and Zhao, Deli and Ge, Xinliang},
	month = mar,
	year = {2007},
	pages = {1547--1553},
	file = {[Zhang.2007] Linear local tangent space alignment and application to face recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhang.2007] Linear local tangent space alignment and application to face recognition.pdf:application/pdf}
}

@inproceedings{he_neighborhood_2005,
	address = {Washington, DC, USA},
	series = {{ICCV} '05},
	title = {Neighborhood {Preserving} {Embedding}},
	booktitle = {Proceedings of the {Tenth} {IEEE} {International} {Conference} on {Computer} {Vision} - {Volume} 2},
	publisher = {IEEE Computer Society},
	author = {He, Xiaofei and Cai, Deng and Yan, Shuicheng and Zhang, Hong-Jiang},
	year = {2005},
	pages = {1208--1213},
	file = {[He.2005] Neighborhood Preserving Embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[He.2005] Neighborhood Preserving Embedding.pdf:application/pdf}
}

@phdthesis{he_locality_2005,
	address = {Chicago, IL, USA},
	type = {{PhD} {Thesis}},
	title = {Locality {Preserving} {Projections}},
	school = {University of Chicago},
	author = {He, Xiaofei},
	year = {2005},
	file = {[He.2005] Locality Preserving Projections.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[He.2005] Locality Preserving Projections.pdf:application/pdf}
}

@incollection{johnson_extensions_1984,
	address = {Providence, Rhode Island},
	title = {Extensions of {Lipschitz} mappings into a {Hilbert} space},
	volume = {26},
	isbn = {978-0-8218-5030-5 978-0-8218-7611-4},
	language = {en},
	booktitle = {Contemporary {Mathematics}},
	publisher = {American Mathematical Society},
	author = {Johnson, William B. and Lindenstrauss, Joram},
	editor = {Beals, Richard and Beck, Anatole and Bellow, Alexandra and Hajian, Arshag},
	year = {1984},
	doi = {10.1090/conm/026/737400},
	pages = {189--206},
	file = {[Johnson.1984] Extensions of Lipschitz mappings into a Hilbert space.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Johnson.1984] Extensions of Lipschitz mappings into a Hilbert space.pdf:application/pdf}
}

@article{kruskal_multidimensional_1964,
	title = {Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis},
	volume = {29},
	number = {1},
	journal = {Psychometrika},
	author = {Kruskal, J. B.},
	month = mar,
	year = {1964},
	pages = {1--27},
	file = {[Kruskal.1964] Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Kruskal.1964] Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis.pdf:application/pdf}
}

@article{hotelling_analysis_1933,
	title = {Analysis of a complex of statistical variables into principal components.},
	volume = {24},
	number = {6},
	journal = {Journal of Educational Psychology},
	author = {Hotelling, H.},
	year = {1933},
	pages = {417--441}
}

@article{sorzano_survey_2014,
	title = {A survey of dimensionality reduction techniques},
	journal = {ArXiv e-prints},
	author = {Sorzano, C. O. S. and Vargas, J. and Montano, A. P.},
	year = {2014},
	keywords = {Computer Science - Learning, Statistics - Machine Learning, Quantitative Biology - Quantitative Methods},
	file = {[Sorzano.2014] A survey of dimensionality reduction techniques.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Sorzano.2014] A survey of dimensionality reduction techniques.pdf:application/pdf}
}

@article{spearman_general_1904,
	title = {"{General} {Intelligence}," {Objectively} {Determined} and {Measured}},
	volume = {15},
	number = {2},
	journal = {The American Journal of Psychology},
	author = {Spearman, C.},
	month = apr,
	year = {1904},
	pages = {201}
}

@book{ma_manifold_2012,
	address = {Boca Raton, Fla. : London},
	title = {Manifold learning theory and applications},
	isbn = {978-1-4398-7109-6},
	publisher = {CRC ; Taylor \& Francis [distributor]},
	editor = {Ma, Yunqian and Fu, Yun},
	year = {2012},
	keywords = {Manifolds (Mathematics)},
	file = {[Ma.2012] Manifold learning theory and applications.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Ma.2012] Manifold learning theory and applications.pdf:application/pdf}
}

@article{grassberger_measuring_1983,
	title = {Measuring the strangeness of strange attractors},
	volume = {9},
	number = {1-2},
	journal = {Physica D: Nonlinear Phenomena},
	author = {Grassberger, Peter and Procaccia, Itamar},
	month = oct,
	year = {1983},
	pages = {189--208}
}

@article{camastra_intrinsic_2016,
	title = {Intrinsic dimension estimation: {Advances} and open problems},
	volume = {328},
	journal = {Information Sciences},
	author = {Camastra, Francesco and Staiano, Antonino},
	month = jan,
	year = {2016},
	pages = {26--41},
	file = {[Camastra.2016] Intrinsic dimension estimation.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Camastra.2016] Intrinsic dimension estimation.pdf:application/pdf}
}

@article{granata_accurate_2016,
	title = {Accurate {Estimation} of the {Intrinsic} {Dimension} {Using} {Graph} {Distances}: {Unraveling} the {Geometric} {Complexity} of {Datasets}},
	volume = {6},
	number = {1},
	journal = {Scientific Reports},
	author = {Granata, Daniele and Carnevale, Vincenzo},
	month = nov,
	year = {2016}
}

@book{ott_chaos_2002,
	address = {Cambridge, U.K. ; New York},
	edition = {2nd ed},
	title = {Chaos in dynamical systems},
	isbn = {978-0-521-81196-5 978-0-521-01084-9},
	publisher = {Cambridge University Press},
	author = {Ott, Edward},
	year = {2002},
	keywords = {Chaotic behavior in systems}
}

@article{pestov_axiomatic_2008,
	title = {An axiomatic approach to intrinsic dimension of a dataset},
	volume = {21},
	number = {2-3},
	journal = {Neural Networks},
	author = {Pestov, Vladimir},
	month = mar,
	year = {2008},
	pages = {204--213},
	file = {[Pestov.2008] An axiomatic approach to intrinsic dimension of a dataset.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Pestov.2008] An axiomatic approach to intrinsic dimension of a dataset.pdf:application/pdf}
}

@article{camastra_data_2003,
	title = {Data dimensionality estimation methods: a survey},
	volume = {36},
	number = {12},
	journal = {Pattern Recognition},
	author = {Camastra, Francesco},
	month = dec,
	year = {2003},
	pages = {2945--2954},
	file = {[Camastra.2003] Data dimensionality estimation methods.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Camastra.2003] Data dimensionality estimation methods.pdf:application/pdf}
}

@article{weinberger_unsupervised_2006,
	title = {Unsupervised {Learning} of {Image} {Manifolds} by {Semidefinite} {Programming}},
	volume = {70},
	number = {1},
	journal = {International Journal of Computer Vision},
	author = {Weinberger, Kilian Q. and Saul, Lawrence K.},
	month = oct,
	year = {2006},
	pages = {77--90},
	file = {[Weinberger.2006] Unsupervised Learning of Image Manifolds by Semidefinite Programming.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Weinberger.2006] Unsupervised Learning of Image Manifolds by Semidefinite Programming.pdf:application/pdf}
}

@article{sammon_nonlinear_1969,
	title = {A {Nonlinear} {Mapping} for {Data} {Structure} {Analysis}},
	volume = {C-18},
	number = {5},
	journal = {IEEE Transactions on Computers},
	author = {Sammon, J.W.},
	month = may,
	year = {1969},
	pages = {401--409},
	file = {[Sammon.1969] A Nonlinear Mapping for Data Structure Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Sammon.1969] A Nonlinear Mapping for Data Structure Analysis.pdf:application/pdf}
}

@incollection{scholkopf_kernel_1997,
	address = {Berlin, Heidelberg},
	title = {Kernel principal component analysis},
	volume = {1327},
	isbn = {978-3-540-63631-1 978-3-540-69620-9},
	booktitle = {Artificial {Neural} {Networks} — {ICANN}'97},
	publisher = {Springer Berlin Heidelberg},
	author = {Schölkopf, Bernhard and Smola, Alexander and Müller, Klaus-Robert},
	editor = {Goos, Gerhard and Hartmanis, Juris and van Leeuwen, Jan and Gerstner, Wulfram and Germond, Alain and Hasler, Martin and Nicoud, Jean-Daniel},
	year = {1997},
	doi = {10.1007/BFb0020217},
	pages = {583--588},
	file = {[Schölkopf.1997] Kernel principal component analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Schölkopf.1997] Kernel principal component analysis.pdf:application/pdf}
}

@incollection{silva_global_2002,
	address = {Cambridge, MA},
	title = {Global {Versus} {Local} {Methods} in {Nonlinear} {Dimensionality} {Reduction}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 15},
	publisher = {MIT Press},
	author = {Silva, Vin D. and Tenenbaum, Joshua B.},
	editor = {Thrun, S. and Obermayer, K.},
	year = {2002},
	pages = {705--712},
	file = {[Silva.2002] Global Versus Local Methods in Nonlinear Dimensionality Reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Silva.2002] Global Versus Local Methods in Nonlinear Dimensionality Reduction.pdf:application/pdf}
}

@article{lee_landmark_2009,
	title = {Landmark {MDS} ensemble},
	volume = {42},
	number = {9},
	journal = {Pattern Recognition},
	author = {Lee, Seunghak and Choi, Seungjin},
	month = sep,
	year = {2009},
	pages = {2045--2053},
	file = {[Lee.2009] Landmark MDS ensemble.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Lee.2009] Landmark MDS ensemble.pdf:application/pdf}
}

@article{vonluxburg_tutorial_2007,
	title = {A tutorial on spectral clustering},
	volume = {17},
	number = {4},
	journal = {Statistics and Computing},
	author = {von Luxburg, Ulrike},
	month = dec,
	year = {2007},
	keywords = {Statistics, Mathematics, Artificial Intelligence (incl. Robotics), Graph Laplacian, Numeric Computing, Spectral clustering, Statistics and Computing/Statistics Programs, general},
	pages = {395--416},
	file = {[von Luxburg.2007] A tutorial on spectral clustering.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[von Luxburg.2007] A tutorial on spectral clustering.pdf:application/pdf;[von Luxburg.2007] A tutorial on spectral clustering.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[von Luxburg.2007] A tutorial on spectral clustering2.pdf:application/pdf}
}

@article{coifman_geometric_2005,
	title = {Geometric diffusions as a tool for harmonic analysis and structure definition of data: {Multiscale} methods},
	volume = {102},
	number = {21},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Coifman, R. R. and Lafon, S. and Lee, A. B. and Maggioni, M. and Nadler, B. and Warner, F. and Zucker, S. W.},
	month = may,
	year = {2005},
	pages = {7432--7437},
	file = {[Coifman.2005] Geometric diffusions as a tool for harmonic analysis and structure definition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Coifman.2005] Geometric diffusions as a tool for harmonic analysis and structure definition.pdf:application/pdf}
}

@article{coifman_diffusion_2006,
	title = {Diffusion maps},
	volume = {21},
	number = {1},
	journal = {Applied and Computational Harmonic Analysis},
	author = {Coifman, Ronald R. and Lafon, Stéphane},
	month = jul,
	year = {2006},
	pages = {5--30},
	file = {[Coifman.2006] Diffusion maps.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Coifman.2006] Diffusion maps.pdf:application/pdf}
}

@inproceedings{belkin_convergence_2006,
	title = {Convergence of laplacian eigenmaps},
	booktitle = {In {NIPS}},
	author = {Belkin, Mikhail and Niyogi, Partha},
	year = {2006},
	file = {[Belkin.2006] Convergence of laplacian eigenmaps.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Belkin.2006] Convergence of laplacian eigenmaps.pdf:application/pdf}
}

@article{belkin_laplacian_2003,
	title = {Laplacian {Eigenmaps} for {Dimensionality} {Reduction} and {Data} {Representation}},
	volume = {15},
	number = {6},
	journal = {Neural Computation},
	author = {Belkin, Mikhail and Niyogi, Partha},
	month = jun,
	year = {2003},
	pages = {1373--1396},
	file = {[Belkin.2003] Laplacian Eigenmaps for Dimensionality Reduction and Data Representation.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Belkin.2003] Laplacian Eigenmaps for Dimensionality Reduction and Data Representation.pdf:application/pdf}
}

@incollection{hinton_stochastic_2003,
	title = {Stochastic {Neighbor} {Embedding}},
	url = {http://papers.nips.cc/paper/2276-stochastic-neighbor-embedding.pdf},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 15},
	publisher = {MIT Press},
	author = {Hinton, Geoffrey E. and Roweis, Sam T.},
	editor = {Becker, S. and Thrun, S. and Obermayer, K.},
	year = {2003},
	pages = {857--864},
	file = {[Hinton.2003] Stochastic Neighbor Embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Hinton.2003] Stochastic Neighbor Embedding.pdf:application/pdf}
}

@article{roweis_nonlinear_2000,
	title = {Nonlinear {Dimensionality} {Reduction} by {Locally} {Linear} {Embedding}},
	volume = {290},
	number = {5500},
	journal = {Science},
	author = {Roweis, S. T.},
	month = dec,
	year = {2000},
	pages = {2323--2326},
	file = {[Roweis.2000] Nonlinear Dimensionality Reduction by Locally Linear Embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Roweis.2000] Nonlinear Dimensionality Reduction by Locally Linear Embedding.pdf:application/pdf}
}

@article{vandermaaten_dimensionality_2009,
	title = {Dimensionality reduction: {A} comparative review},
	journal = {Technical Report TiCC TR 2009-005},
	author = {Van der Maaten, LJP and Postma, EO and Van den Herik, HJ},
	year = {2009},
	file = {[Van der Maaten.2009] Dimensionality reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Van der Maaten.2009] Dimensionality reduction.pdf:application/pdf}
}

@article{vandermaaten_visualizing_2008,
	title = {Visualizing data using t-{SNE}},
	volume = {9},
	number = {2579-2605},
	journal = {The Journal of Machine Learning Research},
	author = {van der Maaten, Laurens and Hinton, Geoffrey},
	year = {2008},
	pages = {85},
	file = {[van der Maaten.2008] Visualizing data using t-SNE.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[van der Maaten.2008] Visualizing data using t-SNE.pdf:application/pdf}
}

@article{vandermaaten_learning_2009,
	title = {Learning a parametric embedding by preserving local structure},
	journal = {Proceedings of AI-STATS},
	author = {van der Maaten, Laurens},
	year = {2009},
	file = {[van der Maaten.2009] Learning a parametric embedding by preserving local structure.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[van der Maaten.2009] Learning a parametric embedding by preserving local structure.pdf:application/pdf}
}

@inproceedings{bengio_outofsample_2003,
	title = {Out-of-{Sample} {Extensions} for {LLE}, {Isomap}, {MDS}, {Eigenmaps}, and {Spectral} {Clustering}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 16 [{Neural} {Information} {Processing} {Systems}, {NIPS} 2003, {December} 8-13, 2003, {Vancouver} and {Whistler}, {British} {Columbia}, {Canada}]},
	author = {Bengio, Yoshua and Paiement, Jean-François and Vincent, Pascal and Delalleau, Olivier and Roux, Nicolas Le and Ouimet, Marie},
	year = {2003},
	pages = {177--184},
	file = {[Bengio.2003] Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Bengio.2003] Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral.pdf:application/pdf}
}

@incollection{silva_global_2003,
	title = {Global {Versus} {Local} {Methods} in {Nonlinear} {Dimensionality} {Reduction}},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 15},
	publisher = {MIT Press},
	author = {Silva, Vin D. and Tenenbaum, Joshua B.},
	editor = {Becker, S. and Thrun, S. and Obermayer, K.},
	year = {2003},
	pages = {721--728}
}

@inproceedings{li_very_2006,
	address = {New York, NY, USA},
	series = {{KDD} '06},
	title = {Very {Sparse} {Random} {Projections}},
	booktitle = {Proceedings of the 12th {ACM} {SIGKDD} {International} {Conference} on {Knowledge} {Discovery} and {Data} {Mining}},
	publisher = {ACM},
	author = {Li, Ping and Hastie, Trevor J. and Church, Kenneth W.},
	year = {2006},
	keywords = {random projections, rates of convergence, sampling},
	pages = {287--296}
}

@book{fukunaga_introduction_1990,
	address = {Boston},
	edition = {2nd ed},
	series = {Computer science and scientific computing},
	title = {Introduction to statistical pattern recognition},
	isbn = {978-0-12-269851-4},
	publisher = {Academic Press},
	author = {Fukunaga, Keinosuke},
	year = {1990},
	keywords = {Mathematical statistics, Statistical methods, Pattern perception, Mathematical models, Decision making}
}

@article{fisher_use_1936,
	title = {{THE} {USE} {OF} {MULTIPLE} {MEASUREMENTS} {IN} {TAXONOMIC} {PROBLEMS}},
	volume = {7},
	number = {2},
	journal = {Annals of Eugenics},
	author = {Fisher, R. A.},
	month = sep,
	year = {1936},
	pages = {179--188}
}

@book{hyvarinen_independent_2001,
	address = {New York},
	title = {Independent component analysis},
	isbn = {978-0-471-40540-5},
	publisher = {J. Wiley},
	author = {Hyvarinen, Aapo and Karhunen, Juha and Oja, Erkki},
	year = {2001},
	keywords = {Independent component analysis},
	file = {[Hyvarinen.2001] Independent component analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Hyvarinen.2001] Independent component analysis.pdf:application/pdf}
}

@article{jenssen_kernel_2010,
	title = {Kernel {Entropy} {Component} {Analysis}},
	volume = {32},
	number = {5},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	author = {Jenssen, R.},
	month = may,
	year = {2010},
	pages = {847--860},
	file = {[Jenssen.2010] Kernel Entropy Component Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Jenssen.2010] Kernel Entropy Component Analysis.pdf:application/pdf}
}

@inproceedings{walder_diffeomorphic_2009,
	address = {Red Hook, NY, USA},
	title = {Diffeomorphic {Dimensionality} {Reduction}},
	booktitle = {Advances in neural information processing systems 21},
	publisher = {Biologische Kybernetik},
	author = {Walder, C. and Schölkopf, B.},
	year = {2009},
	pages = {1713--1720},
	file = {[Walder.2009] Diffeomorphic Dimensionality Reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Walder.2009] Diffeomorphic Dimensionality Reduction.pdf:application/pdf}
}

@inproceedings{cayton_robust_2006,
	address = {New York, NY, USA},
	series = {{ICML} '06},
	title = {Robust {Euclidean} {Embedding}},
	booktitle = {Proceedings of the 23rd {International} {Conference} on {Machine} {Learning}},
	publisher = {ACM},
	author = {Cayton, Lawrence and Dasgupta, Sanjoy},
	year = {2006},
	pages = {169--176},
	file = {[Cayton.2006] Robust Euclidean Embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Cayton.2006] Robust Euclidean Embedding.pdf:application/pdf}
}

@article{daspremont_direct_2007,
	title = {A {Direct} {Formulation} for {Sparse} {PCA} {Using} {Semidefinite} {Programming}},
	volume = {49},
	number = {3},
	journal = {SIAM Review},
	author = {d'Aspremont, Alexandre and El Ghaoui, Laurent and Jordan, Michael I. and Lanckriet, Gert R. G.},
	month = jan,
	year = {2007},
	pages = {434--448},
	file = {[d'Aspremont.2007] A Direct Formulation for Sparse PCA Using Semidefinite Programming.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[d'Aspremont.2007] A Direct Formulation for Sparse PCA Using Semidefinite Programming.pdf:application/pdf}
}

@article{zou_sparse_2006,
	title = {Sparse {Principal} {Component} {Analysis}},
	volume = {15},
	number = {2},
	journal = {Journal of Computational and Graphical Statistics},
	author = {Zou, Hui and Hastie, Trevor and Tibshirani, Robert},
	month = jun,
	year = {2006},
	pages = {265--286},
	file = {[Zou.2006] Sparse Principal Component Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zou.2006] Sparse Principal Component Analysis.pdf:application/pdf}
}

@inproceedings{cai_locality_2007,
	address = {San Francisco, CA, USA},
	series = {{IJCAI}'07},
	title = {Locality {Sensitive} {Discriminant} {Analysis}},
	booktitle = {Proceedings of the 20th {International} {Joint} {Conference} on {Artifical} {Intelligence}},
	publisher = {Morgan Kaufmann Publishers Inc.},
	author = {Cai, Deng and He, Xiaofei and Zhou, Kun and Han, Jiawei and Bao, Hujun},
	year = {2007},
	pages = {708--713},
	file = {[Cai.2007] Locality Sensitive Discriminant Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Cai.2007] Locality Sensitive Discriminant Analysis.pdf:application/pdf}
}

@article{xiaofeihe_learning_2008,
	title = {Learning a {Maximum} {Margin} {Subspace} for {Image} {Retrieval}},
	volume = {20},
	number = {2},
	journal = {IEEE Transactions on Knowledge and Data Engineering},
	author = {{Xiaofei He} and {Deng Cai} and {Jiawei Han}},
	month = feb,
	year = {2008},
	pages = {189--201},
	file = {[Xiaofei He.2008] Learning a Maximum Margin Subspace for Image Retrieval.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Xiaofei He.2008] Learning a Maximum Margin Subspace for Image Retrieval.pdf:application/pdf}
}

@inproceedings{cai_isometric_2007,
	address = {Vancouver, British Columbia, Canada},
	series = {{AAAI}'07},
	title = {Isometric {Projection}},
	isbn = {978-1-57735-323-2},
	booktitle = {Proceedings of the {22Nd} {National} {Conference} on {Artificial} {Intelligence} - {Volume} 1},
	publisher = {AAAI Press},
	author = {Cai, Deng and He, Xiaofei and Han, Jiawei},
	year = {2007},
	pages = {528--533},
	file = {[Cai.2007] Isometric Projection.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Cai.2007] Isometric Projection.pdf:application/pdf}
}

@article{cai_orthogonal_2006,
	title = {Orthogonal {Laplacianfaces} for {Face} {Recognition}},
	volume = {15},
	number = {11},
	journal = {IEEE Transactions on Image Processing},
	author = {Cai, D. and He, X. and Han, J. and Zhang, H.-J.},
	month = nov,
	year = {2006},
	pages = {3608--3614},
	file = {[Cai.2006] Orthogonal Laplacianfaces for Face Recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Cai.2006] Orthogonal Laplacianfaces for Face Recognition.pdf:application/pdf}
}

@article{barker_partial_2003,
	title = {Partial least squares for discrimination},
	volume = {17},
	number = {3},
	journal = {Journal of Chemometrics},
	author = {Barker, Matthew and Rayens, William},
	month = mar,
	year = {2003},
	pages = {166--173},
	file = {[Barker.2003] Partial least squares for discrimination.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Barker.2003] Partial least squares for discrimination.pdf:application/pdf}
}

@article{hotelling_relations_1936,
	title = {{RELATIONS} {BETWEEN} {TWO} {SETS} {OF} {VARIATES}},
	volume = {28},
	number = {3-4},
	journal = {Biometrika},
	author = {Hotelling, H.},
	month = dec,
	year = {1936},
	pages = {321--377},
	file = {[Hotelling.1936] RELATIONS BETWEEN TWO SETS OF VARIATES.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Hotelling.1936] RELATIONS BETWEEN TWO SETS OF VARIATES.pdf:application/pdf}
}

@book{borga_unified_1997,
	address = {Linköping, Sweden},
	title = {A {Unified} {Approach} to {PCA}, {PLS}, {MLR} and {CCA}},
	isbn = {9925-7521-8-3},
	publisher = {Linköping University, Department of Electrical Engineering},
	author = {Borga, Magnus and Landelius, Tomas and Knutsson, Hans},
	year = {1997},
	file = {[Borga.1997] A Unified Approach to PCA, PLS, MLR and CCA.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Borga.1997] A Unified Approach to PCA, PLS, MLR and CCA.pdf:application/pdf}
}

@incollection{rosipal_overview_2006,
	address = {Berlin, Heidelberg},
	title = {Overview and {Recent} {Advances} in {Partial} {Least} {Squares}},
	isbn = {978-3-540-34138-3},
	booktitle = {Subspace, {Latent} {Structure} and {Feature} {Selection}: {Statistical} and {Optimization} {Perspectives} {Workshop}, {SLSFS} 2005, {Bohinj}, {Slovenia}, {February} 23-25, 2005, {Revised} {Selected} {Papers}},
	publisher = {Springer Berlin Heidelberg},
	author = {Rosipal, Roman and Krämer, Nicole},
	editor = {Saunders, Craig and Grobelnik, Marko and Gunn, Steve and Shawe-Taylor, John},
	year = {2006},
	doi = {10.1007/11752790_2},
	pages = {34--51},
	file = {[Rosipal.2006] Overview and Recent Advances in Partial Least Squares.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Rosipal.2006] Overview and Recent Advances in Partial Least Squares.pdf:application/pdf}
}

@incollection{wold_path_1975,
	title = {Path {Models} with {Latent} {Variables}: {The} {NIPALS} {Approach}},
	isbn = {978-0-12-103950-9},
	language = {en},
	booktitle = {Quantitative {Sociology}},
	publisher = {Elsevier},
	author = {Wold, Herman},
	year = {1975},
	doi = {10.1016/B978-0-12-103950-9.50017-4},
	pages = {307--357}
}

@article{noonan_nipals_1977,
	title = {{NIPALS} {Path} {Modelling} with {Latent} {Variables}: {Analysing} {School} {Survey} {Data} {Using} {Nonlinear} {Iterative} {Partial} {Least} {Squares} $^{\textrm{1}}$\$},
	volume = {21},
	number = {1},
	journal = {Scandinavian Journal of Educational Research},
	author = {Noonan, Richard and Wold, Herman},
	month = jan,
	year = {1977},
	pages = {33--61}
}

@article{candes_robust_2011,
	title = {Robust principal component analysis?},
	volume = {58},
	number = {3},
	journal = {Journal of the ACM},
	author = {Candès, Emmanuel J. and Li, Xiaodong and Ma, Yi and Wright, John},
	month = may,
	year = {2011},
	pages = {1--37},
	file = {[Candès.2011] Robust principal component analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Candès.2011] Robust principal component analysis.pdf:application/pdf}
}

@inproceedings{bishop_bayesian_1999,
	title = {Bayesian {PCA}},
	volume = {11},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
	publisher = {MIT Press},
	author = {Bishop, Christopher},
	month = jan,
	year = {1999},
	pages = {382--388},
	file = {[Bishop.1999] Bayesian PCA.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Bishop.1999] Bayesian PCA.pdf:application/pdf}
}

@article{tipping_probabilistic_1999,
	title = {Probabilistic {Principal} {Component} {Analysis}},
	volume = {61},
	number = {3},
	journal = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
	author = {Tipping, Michael E. and Bishop, Christopher M.},
	month = aug,
	year = {1999},
	pages = {611--622},
	file = {[Tipping.1999] Probabilistic Principal Component Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Tipping.1999] Probabilistic Principal Component Analysis.pdf:application/pdf}
}

@article{arenas-garcia_kernel_2013,
	title = {Kernel {Multivariate} {Analysis} {Framework} for {Supervised} {Subspace} {Learning}: {A} {Tutorial} on {Linear} and {Kernel} {Multivariate} {Methods}},
	volume = {30},
	number = {4},
	journal = {IEEE Signal Processing Magazine},
	author = {Arenas-Garcia, Jeronimo and Petersen, Kaare Brandt and Camps-Valls, Gustavo and Hansen, Lars Kai},
	month = jul,
	year = {2013},
	pages = {16--29},
	file = {[Arenas-Garcia.2013] Kernel Multivariate Analysis Framework for Supervised Subspace Learning.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Arenas-Garcia.2013] Kernel Multivariate Analysis Framework for Supervised Subspace Learning.pdf:application/pdf}
}

@inproceedings{shaw_minimum_2007,
	title = {Minimum {Volume} {Embedding}},
	volume = {2 of JMLR: W\&CP},
	booktitle = {Proceedings of the {Eleventh} {International} {Conference} on {Artificial} {Intelligence} and {Statistics} {March} 21-24, 2007, {San} {Juan}, {Puerto} {Rico}},
	author = {Shaw, B. and Jebara, T.},
	editor = {Meila, Marina and Shen, Xiaotong},
	month = mar,
	year = {2007},
	pages = {460--467},
	file = {[Shaw.2007] Minimum Volume Embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Shaw.2007] Minimum Volume Embedding.pdf:application/pdf}
}

@inproceedings{wang_feature_2007,
	title = {Feature {Extraction} by {Maximizing} the {Average} {Neighborhood} {Margin}},
	booktitle = {2007 {IEEE} {Conference} on {Computer} {Vision} and {Pattern} {Recognition}},
	author = {Wang, F. and Zhang, C.},
	month = jun,
	year = {2007},
	keywords = {Data mining, ANMM, average neighborhood margin maximization, computer vision, Computer vision, Covariance matrix, face recognition, feature extraction, Feature extraction, Kernel, linear discriminant analysis, Linear discriminant analysis, optimisation, Pattern recognition, Principal component analysis, Scattering, supervised linear feature extraction, Tensile stress},
	pages = {1--8},
	file = {[Wang.2007] Feature Extraction by Maximizing the Average Neighborhood Margin.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Wang.2007] Feature Extraction by Maximizing the Average Neighborhood Margin.pdf:application/pdf}
}

@inproceedings{goldberger_neighbourhood_2004,
	title = {Neighbourhood components analysis},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 17},
	publisher = {MIT Press},
	author = {Goldberger, Jacob and Roweis, Sam and Hinton, Geoff and Salakhutdinov, Ruslan},
	year = {2004},
	pages = {513--520},
	file = {[Goldberger.2004] Neighbourhood components analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Goldberger.2004] Neighbourhood components analysis.pdf:application/pdf}
}

@article{wang_survey_2015,
	title = {Survey on distance metric learning and dimensionality reduction in data mining},
	volume = {29},
	number = {2},
	journal = {Data Mining and Knowledge Discovery},
	author = {Wang, Fei and Sun, Jimeng},
	month = mar,
	year = {2015},
	pages = {534--564},
	file = {[Wang.2015] Survey on distance metric learning and dimensionality reduction in data mining.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Wang.2015] Survey on distance metric learning and dimensionality reduction in data mining.pdf:application/pdf}
}

@article{einbeck_representing_2007,
	title = {Representing complex data using localized principal components with application to astronomical data},
	journal = {ArXiv e-prints},
	author = {Einbeck, J. and Evers, L. and Bailer-Jones, C.},
	year = {2007},
	keywords = {Astrophysics},
	file = {[Einbeck.2007] Representing complex data using localized principal components with application.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Einbeck.2007] Representing complex data using localized principal components with application.pdf:application/pdf}
}

@techreport{engel_survey_2012,
	title = {A {Survey} of {Dimension} {Reduction} {Methods} for {High}-dimensional {Data} {Analysis} and {Visualization}},
	language = {eng},
	institution = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany},
	author = {Engel, Daniel and Hüttenberger, Lars and Hamann, Bernd and Herbstritt, Marc},
	year = {2012},
	doi = {10.4230/OASIcs.VLUDS.2011.135},
	file = {[Engel.2012] A Survey of Dimension Reduction Methods for High-dimensional Data Analysis and.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Engel.2012] A Survey of Dimension Reduction Methods for High-dimensional Data Analysis and.pdf:application/pdf}
}

@article{zheng_gabor_2007,
	title = {Gabor feature-based face recognition using supervised locality preserving projection},
	volume = {87},
	number = {10},
	journal = {Signal Processing},
	author = {Zheng, Zhonglong and Yang, Fan and Tan, Wenan and Jia, Jiong and Yang, Jie},
	month = oct,
	year = {2007},
	pages = {2473--2483},
	file = {[Zheng.2007] Gabor feature-based face recognition using supervised locality preserving.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zheng.2007] Gabor feature-based face recognition using supervised locality preserving.pdf:application/pdf}
}

@inproceedings{shikkenawis_improving_2012,
	title = {Improving the {Locality} {Preserving} {Projection} for dimensionality reduction},
	booktitle = {2012 {Third} {International} {Conference} on {Emerging} {Applications} of {Information} {Technology}},
	publisher = {IEEE},
	author = {Shikkenawis, Gitam and Mitra, Suman K.},
	month = nov,
	year = {2012},
	pages = {161--164},
	file = {[Shikkenawis.2012] Improving the Locality Preserving Projection for dimensionality reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Shikkenawis.2012] Improving the Locality Preserving Projection for dimensionality reduction.pdf:application/pdf}
}

@article{zhang_maximum_2007,
	title = {Maximum variance projections for face recognition},
	volume = {46},
	number = {6},
	journal = {Optical Engineering},
	author = {Zhang, Tianhao},
	month = jun,
	year = {2007},
	pages = {067206},
	file = {[Zhang.2007] Maximum variance projections for face recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhang.2007] Maximum variance projections for face recognition.pdf:application/pdf}
}

@article{yang_globally_2007,
	title = {Globally {Maximizing}, {Locally} {Minimizing}: {Unsupervised} {Discriminant} {Projection} with {Applications} to {Face} and {Palm} {Biometrics}},
	volume = {29},
	number = {4},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	author = {Yang, Jian and Zhang, David and Yang, Jing-yu and Niu, Ben},
	month = apr,
	year = {2007},
	pages = {650--664},
	file = {[Yang.2007] Globally Maximizing, Locally Minimizing.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Yang.2007] Globally Maximizing, Locally Minimizing.pdf:application/pdf}
}

@inproceedings{lee_curvilinear_2002,
	title = {Curvilinear {Distance} {Analysis} versus {Isomap}},
	booktitle = {{ESANN}},
	author = {Lee, John Aldo and Lendasse, Amaury and Verleysen, Michel},
	year = {2002},
	file = {[Lee.2002] Curvilinear Distance Analysis versus Isomap.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Lee.2002] Curvilinear Distance Analysis versus Isomap.pdf:application/pdf}
}

@incollection{herault_curvilinear_1999,
	address = {Berlin, Heidelberg},
	title = {Curvilinear component analysis for high-dimensional data representation: {I}. {Theoretical} aspects and practical use in the presence of noise},
	volume = {1607},
	isbn = {978-3-540-66068-2 978-3-540-48772-2},
	booktitle = {Engineering {Applications} of {Bio}-{Inspired} {Artificial} {Neural} {Networks}},
	publisher = {Springer Berlin Heidelberg},
	author = {Hérault, Jeanny and Jausions-Picaud, Claire and Guérin-Dugué, Anne},
	editor = {Goos, Gerhard and Hartmanis, Juris and van Leeuwen, Jan and Mira, José and Sánchez-Andrés, Juan V.},
	year = {1999},
	doi = {10.1007/BFb0100530},
	pages = {625--634}
}

@article{demartines_curvilinear_1997,
	title = {Curvilinear component analysis: a self-organizing neural network for nonlinear mapping of data sets},
	volume = {8},
	number = {1},
	journal = {IEEE Transactions on Neural Networks},
	author = {Demartines, P. and Herault, J.},
	month = jan,
	year = {1997},
	pages = {148--154},
	file = {[Demartines.1997] Curvilinear component analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Demartines.1997] Curvilinear component analysis.pdf:application/pdf}
}

@article{lee_nonlinear_2004,
	title = {Nonlinear projection with curvilinear distances: {Isomap} versus curvilinear distance analysis},
	volume = {57},
	journal = {Neurocomputing},
	author = {Lee, John Aldo and Lendasse, Amaury and Verleysen, Michel},
	month = mar,
	year = {2004},
	pages = {49--76},
	file = {[Lee.2004] Nonlinear projection with curvilinear distances.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Lee.2004] Nonlinear projection with curvilinear distances.pdf:application/pdf}
}

@book{borg_modern_2010,
	address = {New York, NY},
	title = {Modern multidimensional scaling: theory and applications},
	isbn = {978-1-4419-2046-1 978-0-387-28981-6},
	language = {English},
	publisher = {Springer New York},
	author = {Borg, Ingwer and Groenen, Patrick J. F},
	year = {2010}
}

@book{borg_modern_2010a,
	address = {New York, NY},
	title = {Modern multidimensional scaling: theory and applications},
	isbn = {978-1-4419-2046-1 978-0-387-28981-6},
	language = {English},
	publisher = {Springer New York},
	author = {Borg, Ingwer and Groenen, Patrick J. F},
	year = {2010}
}

@article{france_twoway_2011,
	title = {Two-{Way} {Multidimensional} {Scaling}: {A} {Review}},
	volume = {41},
	number = {5},
	journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)},
	author = {France, Stephen L. and Carroll, J. Douglas},
	month = sep,
	year = {2011},
	pages = {644--661}
}

@article{kambhatla_dimension_1997,
	title = {Dimension {Reduction} by {Local} {Principal} {Component} {Analysis}},
	volume = {9},
	number = {7},
	journal = {Neural Computation},
	author = {Kambhatla, Nandakishore and Leen, Todd K.},
	month = oct,
	year = {1997},
	pages = {1493--1516},
	file = {[Kambhatla.1997] Dimension Reduction by Local Principal Component Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Kambhatla.1997] Dimension Reduction by Local Principal Component Analysis.pdf:application/pdf}
}

@article{agrafiotis_selforganizing_2002,
	title = {A self-organizing principle for learning nonlinear manifolds},
	volume = {99},
	number = {25},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Agrafiotis, D. K. and Xu, H.},
	month = dec,
	year = {2002},
	pages = {15869--15872},
	file = {[Agrafiotis.2002] A self-organizing principle for learning nonlinear manifolds.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Agrafiotis.2002] A self-organizing principle for learning nonlinear manifolds.pdf:application/pdf}
}

@article{agrafiotis_stochastic_2010,
	title = {Stochastic {Proximity} {Embedding}: {Methods} and {Applications}},
	volume = {29},
	number = {11},
	journal = {Molecular Informatics},
	author = {Agrafiotis, Dimitris K. and Xu, Huafeng and Zhu, Fangqiang and Bandyopadhyay, Deepak and Liu, Pu},
	month = nov,
	year = {2010},
	pages = {758--770},
	file = {[Agrafiotis.2010] Stochastic Proximity Embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Agrafiotis.2010] Stochastic Proximity Embedding.pdf:application/pdf}
}

@article{agrafiotis_stochastic_2003,
	title = {Stochastic proximity embedding},
	volume = {24},
	number = {10},
	journal = {Journal of Computational Chemistry},
	author = {Agrafiotis, Dimitris K.},
	month = jul,
	year = {2003},
	pages = {1215--1221},
	file = {[Agrafiotis.2003] Stochastic proximity embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Agrafiotis.2003] Stochastic proximity embedding.pdf:application/pdf}
}

@inproceedings{boutet_being_2016,
	title = {Being prepared in a sparse world: {The} case of {KNN} graph construction},
	booktitle = {{ICDE} 2016},
	publisher = {IEEE},
	author = {Boutet, Antoine and Kermarrec, Anne-Marie and Mittal, Nupur and Taiani, Francois},
	month = may,
	year = {2016},
	pages = {241--252},
	file = {[Boutet.2016] Being prepared in a sparse world.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Boutet.2016] Being prepared in a sparse world.pdf:application/pdf}
}

@article{yu_enhanced_2011,
	title = {Enhanced locality preserving projections using robust path based similarity},
	volume = {74},
	number = {4},
	journal = {Neurocomputing},
	author = {Yu, Guoxian and Peng, Hong and Wei, Jia and Ma, Qianli},
	month = jan,
	year = {2011},
	pages = {598--605},
	file = {[Yu.2011] Enhanced locality preserving projections using robust path based similarity.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Yu.2011] Enhanced locality preserving projections using robust path based similarity.pdf:application/pdf}
}

@article{huang_local_2015,
	title = {Local similarity preserving projections for face recognition},
	volume = {69},
	number = {11},
	journal = {AEU - International Journal of Electronics and Communications},
	author = {Huang, Pu and Gao, Guangwei},
	month = nov,
	year = {2015},
	pages = {1724--1732},
	file = {[Huang.2015] Local similarity preserving projections for face recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Huang.2015] Local similarity preserving projections for face recognition.pdf:application/pdf}
}

@article{yang_sampledependent_2010,
	title = {Sample-dependent graph construction with application to dimensionality reduction},
	volume = {74},
	number = {1-3},
	journal = {Neurocomputing},
	author = {Yang, Bo and Chen, Songcan},
	month = dec,
	year = {2010},
	pages = {301--314},
	file = {[Yang.2010] Sample-dependent graph construction with application to dimensionality reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Yang.2010] Sample-dependent graph construction with application to dimensionality reduction.pdf:application/pdf}
}

@inproceedings{hwann-tzongchen_local_2005,
	title = {Local {Discriminant} {Embedding} and {Its} {Variants}},
	volume = {2},
	booktitle = {2005 {IEEE} {Computer} {Society} {Conference} on {Computer} {Vision} and {Pattern} {Recognition}},
	publisher = {IEEE},
	author = {{Hwann-Tzong Chen} and {Huang-Wei Chang} and {Tyng-Luh Liu}},
	year = {2005},
	pages = {846--853},
	file = {[Hwann-Tzong Chen.2005] Local Discriminant Embedding and Its Variants.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Hwann-Tzong Chen.2005] Local Discriminant Embedding and Its Variants.pdf:application/pdf}
}

@article{fu_locally_2005,
	title = {Locally {Linear} {Embedded} {Eigenspace} {Analysis}},
	volume = {2005},
	journal = {IFP-TR, UIUC},
	author = {Fu, Yun and Huang, Thomas S.},
	year = {2005},
	pages = {2--05},
	file = {[Fu.2005] Locally Linear Embedded Eigenspace Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Fu.2005] Locally Linear Embedded Eigenspace Analysis.pdf:application/pdf}
}

@inproceedings{wu_local_2007,
	title = {Local learning projections},
	booktitle = {Proceedings of the 24th international conference on {Machine} learning},
	publisher = {ACM Press},
	author = {Wu, Mingrui and Yu, Kai and Yu, Shipeng and Schölkopf, Bernhard},
	year = {2007},
	pages = {1039--1046},
	file = {[Wu.2007] Local learning projections.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Wu.2007] Local learning projections.pdf:application/pdf}
}

@article{wang_complete_2010,
	title = {Complete neighborhood preserving embedding for face recognition},
	volume = {43},
	number = {3},
	journal = {Pattern Recognition},
	author = {Wang, Yong and Wu, Yi},
	month = mar,
	year = {2010},
	pages = {1008--1015},
	file = {[Wang.2010] Complete neighborhood preserving embedding for face recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Wang.2010] Complete neighborhood preserving embedding for face recognition.pdf:application/pdf}
}

@article{qiao_sparsity_2010,
	title = {Sparsity preserving projections with applications to face recognition},
	volume = {43},
	number = {1},
	journal = {Pattern Recognition},
	author = {Qiao, Lishan and Chen, Songcan and Tan, Xiaoyang},
	month = jan,
	year = {2010},
	pages = {331--341},
	file = {[Qiao.2010] Sparsity preserving projections with applications to face recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Qiao.2010] Sparsity preserving projections with applications to face recognition.pdf:application/pdf}
}

@article{gao_discriminative_2015,
	title = {Discriminative sparsity preserving projections for image recognition},
	volume = {48},
	number = {8},
	journal = {Pattern Recognition},
	author = {Gao, Quanxue and Huang, Yunfang and Zhang, Hailin and Hong, Xin and Li, Kui and Wang, Yong},
	month = aug,
	year = {2015},
	pages = {2543--2553},
	file = {[Gao.2015] Discriminative sparsity preserving projections for image recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Gao.2015] Discriminative sparsity preserving projections for image recognition.pdf:application/pdf}
}

@article{li_efficient_2006,
	title = {Efficient and {Robust} {Feature} {Extraction} by {Maximum} {Margin} {Criterion}},
	volume = {17},
	number = {1},
	journal = {IEEE Transactions on Neural Networks},
	author = {Li, H. and Jiang, T. and Zhang, K.},
	month = jan,
	year = {2006},
	pages = {157--165},
	file = {[Li.2006] Efficient and Robust Feature Extraction by Maximum Margin Criterion.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Li.2006] Efficient and Robust Feature Extraction by Maximum Margin Criterion.pdf:application/pdf}
}

@inproceedings{sugiyama_local_2006,
	title = {Local {Fisher} discriminant analysis for supervised dimensionality reduction},
	booktitle = {Proceedings of the 23rd international conference on {Machine} learning},
	publisher = {ACM Press},
	author = {Sugiyama, Masashi},
	year = {2006},
	pages = {905--912},
	file = {[Sugiyama.2006] Local Fisher discriminant analysis for supervised dimensionality reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Sugiyama.2006] Local Fisher discriminant analysis for supervised dimensionality reduction.pdf:application/pdf}
}

@incollection{zelnik-manor_selftuning_2005,
	title = {Self-{Tuning} {Spectral} {Clustering}},
	url = {http://papers.nips.cc/paper/2619-self-tuning-spectral-clustering.pdf},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 17},
	publisher = {MIT Press},
	author = {Zelnik-manor, Lihi and Perona, Pietro},
	editor = {Saul, L. K. and Weiss, Y. and Bottou, L.},
	year = {2005},
	pages = {1601--1608},
	file = {[Zelnik-manor.2005] Self-Tuning Spectral Clustering.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zelnik-manor.2005] Self-Tuning Spectral Clustering.pdf:application/pdf}
}

@article{li_supervised_2009,
	title = {Supervised feature extraction based on orthogonal discriminant projection},
	volume = {73},
	number = {1-3},
	journal = {Neurocomputing},
	author = {Li, Bo and Wang, Chao and Huang, De-Shuang},
	month = dec,
	year = {2009},
	pages = {191--196},
	file = {[Li.2009] Supervised feature extraction based on orthogonal discriminant projection.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Li.2009] Supervised feature extraction based on orthogonal discriminant projection.pdf:application/pdf}
}

@article{zhang_modified_2011,
	title = {Modified orthogonal discriminant projection for classification},
	volume = {74},
	number = {17},
	journal = {Neurocomputing},
	author = {Zhang, Shanwen and Lei, Ying-Ke and Wu, Yan-Hua and Yang, Jun-An},
	month = oct,
	year = {2011},
	pages = {3690--3694},
	file = {[Zhang.2011] Modified orthogonal discriminant projection for classification.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhang.2011] Modified orthogonal discriminant projection for classification.pdf:application/pdf}
}

@article{dao-qingdai_face_2007,
	title = {Face {Recognition} by {Regularized} {Discriminant} {Analysis}},
	volume = {37},
	number = {4},
	journal = {IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)},
	author = {{Dao-Qing Dai} and Yuen, P.C.},
	month = aug,
	year = {2007},
	pages = {1080--1085},
	file = {[Dao-Qing Dai.2007] Face Recognition by Regularized Discriminant Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Dao-Qing Dai.2007] Face Recognition by Regularized Discriminant Analysis.pdf:application/pdf}
}

@article{friedman_regularized_1989,
	title = {Regularized {Discriminant} {Analysis}},
	volume = {84},
	number = {405},
	journal = {Journal of the American Statistical Association},
	author = {Friedman, Jerome H.},
	month = mar,
	year = {1989},
	pages = {165},
	file = {[Friedman.1989] Regularized Discriminant Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Friedman.1989] Regularized Discriminant Analysis.pdf:application/pdf}
}

@inproceedings{cai_semisupervised_2007,
	title = {Semi-supervised {Discriminant} {Analysis}},
	booktitle = {2007 {IEEE} 11th {International} {Conference} on {Computer} {Vision}},
	publisher = {IEEE},
	author = {Cai, Deng and He, Xiaofei and Han, Jiawei},
	year = {2007},
	pages = {1--7},
	file = {[Cai.2007] Semi-supervised Discriminant Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Cai.2007] Semi-supervised Discriminant Analysis.pdf:application/pdf}
}

@article{zhang_discriminant_2006,
	title = {Discriminant neighborhood embedding for classification},
	volume = {39},
	number = {11},
	journal = {Pattern Recognition},
	author = {Zhang, Wei and Xue, Xiangyang and Lu, Hong and Guo, Yue-Fei},
	month = nov,
	year = {2006},
	pages = {2240--2243},
	file = {[Zhang.2006] Discriminant neighborhood embedding for classification.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhang.2006] Discriminant neighborhood embedding for classification.pdf:application/pdf}
}

@article{ding_double_2015,
	title = {Double adjacency graphs-based discriminant neighborhood embedding},
	volume = {48},
	number = {5},
	journal = {Pattern Recognition},
	author = {Ding, Chuntao and Zhang, Li},
	month = may,
	year = {2015},
	pages = {1734--1742},
	file = {[Ding.2015] Double adjacency graphs-based discriminant neighborhood embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Ding.2015] Double adjacency graphs-based discriminant neighborhood embedding.pdf:application/pdf}
}

@article{yan_graph_2007,
	title = {Graph {Embedding} and {Extensions}: {A} {General} {Framework} for {Dimensionality} {Reduction}},
	volume = {29},
	number = {1},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	author = {Yan, Shuicheng and Xu, Dong and Zhang, Benyu and Zhang, Hong-jiang and Yang, Qiang and Lin, Stephen},
	month = jan,
	year = {2007},
	pages = {40--51},
	file = {[Yan.2007] Graph Embedding and Extensions.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Yan.2007] Graph Embedding and Extensions.pdf:application/pdf}
}

@article{ji_relevance_2016,
	title = {Relevance and irrelevance graph based marginal {Fisher} analysis for image search reranking},
	volume = {121},
	journal = {Signal Processing},
	author = {Ji, Zhong and Pang, Yanwei and Yuan, Yuan and Pan, Jing},
	month = apr,
	year = {2016},
	pages = {139--152},
	file = {[Ji.2016] Relevance and irrelevance graph based marginal Fisher analysis for image search.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Ji.2016] Relevance and irrelevance graph based marginal Fisher analysis for image search.pdf:application/pdf}
}

@article{li_sliced_1991,
	title = {Sliced {Inverse} {Regression} for {Dimension} {Reduction}},
	volume = {86},
	number = {414},
	journal = {Journal of the American Statistical Association},
	author = {Li, Ker-Chau},
	month = jun,
	year = {1991},
	pages = {316},
	file = {[Li.1991] Sliced Inverse Regression for Dimension Reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Li.1991] Sliced Inverse Regression for Dimension Reduction.pdf:application/pdf}
}

@article{zhong_rsir_2005,
	title = {{RSIR}: regularized sliced inverse regression for motif discovery},
	volume = {21},
	number = {22},
	journal = {Bioinformatics},
	author = {Zhong, W. and Zeng, P. and Ma, P. and Liu, J. S. and Zhu, Y.},
	month = nov,
	year = {2005},
	pages = {4169--4175},
	file = {[Zhong.2005] RSIR.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhong.2005] RSIR.pdf:application/pdf}
}

@article{chiaromonte_dimension_2002,
	title = {Dimension reduction strategies for analyzing global gene expression data with a response},
	volume = {176},
	issn = {0025-5564},
	number = {1},
	journal = {Mathematical Biosciences},
	author = {Chiaromonte, Francesca and Martinelli, Jessica},
	year = {2002},
	keywords = {Microarray data, Randomization, Singular value decomposition, Sliced inverse regression, Sufficient dimension reduction},
	pages = {123 -- 144},
	file = {[Chiaromonte.2002] Dimension reduction strategies for analyzing global gene expression data with a.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Chiaromonte.2002] Dimension reduction strategies for analyzing global gene expression data with a.pdf:application/pdf}
}

@article{bernard-michel_gaussian_2009,
	title = {Gaussian {Regularized} {Sliced} {Inverse} {Regression}},
	volume = {19},
	number = {1},
	journal = {Statistics and Computing},
	author = {Bernard-Michel, Caroline and Gardes, Laurent and Girard, Stéphane},
	month = mar,
	year = {2009},
	pages = {85--98},
	file = {[Bernard-Michel.2009] Gaussian Regularized Sliced Inverse Regression.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Bernard-Michel.2009] Gaussian Regularized Sliced Inverse Regression.pdf:application/pdf}
}

@article{bernard-michel_retrieval_2009,
	title = {Retrieval of {Mars} surface physical properties from {OMEGA} hyperspectral images using regularized sliced inverse regression},
	volume = {114},
	number = {E6},
	journal = {Journal of Geophysical Research},
	author = {Bernard-Michel, C. and Douté, S. and Fauvel, M. and Gardes, L. and Girard, S.},
	month = jun,
	year = {2009},
	file = {[Bernard-Michel.2009] Retrieval of Mars surface physical properties from OMEGA hyperspectral images.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Bernard-Michel.2009] Retrieval of Mars surface physical properties from OMEGA hyperspectral images.pdf:application/pdf}
}

@article{wu_localized_2010,
	title = {Localized {Sliced} {Inverse} {Regression}},
	volume = {19},
	number = {4},
	journal = {Journal of Computational and Graphical Statistics},
	author = {Wu, Qiang and Liang, Feng and Mukherjee, Sayan},
	year = {2010},
	pages = {843--860},
	file = {[Wu.2010] Localized Sliced Inverse Regression.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Wu.2010] Localized Sliced Inverse Regression.pdf:application/pdf}
}

@article{denniscook_method_2000,
	title = {Save: a method for dimension reduction and graphics in regression},
	volume = {29},
	number = {9-10},
	journal = {Communications in Statistics - Theory and Methods},
	author = {Dennis Cook, R.},
	month = jan,
	year = {2000},
	pages = {2109--2121},
	file = {[Dennis Cook.2000] Save.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Dennis Cook.2000] Save.pdf:application/pdf}
}

@article{li_directional_2007,
	title = {On {Directional} {Regression} for {Dimension} {Reduction}},
	volume = {102},
	number = {479},
	journal = {Journal of the American Statistical Association},
	author = {Li, Bing and Wang, Shaoli},
	month = sep,
	year = {2007},
	pages = {997--1008},
	file = {[Li.2007] On Directional Regression for Dimension Reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Li.2007] On Directional Regression for Dimension Reduction.pdf:application/pdf}
}

@inproceedings{ding_adaptive_2007,
	title = {Adaptive dimension reduction using discriminant analysis and {K}-means clustering},
	booktitle = {Proceedings of the 24th international conference on {Machine} learning},
	publisher = {ACM Press},
	author = {Ding, Chris and Li, Tao},
	year = {2007},
	pages = {521--528},
	file = {[Ding.2007] Adaptive dimension reduction using discriminant analysis and K-means clustering.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Ding.2007] Adaptive dimension reduction using discriminant analysis and K-means clustering.pdf:application/pdf}
}

@inproceedings{ding_adaptive_2002,
	title = {Adaptive dimension reduction for clustering high dimensional data},
	booktitle = {Proceedings 2002 {IEEE} {International} {Conference} on {Data} {Mining}},
	publisher = {IEEE Comput. Soc},
	author = {Ding, C. and {Xiaofeng He} and {Hongyuan Zha} and Simon, H.D.},
	year = {2002},
	pages = {147--154},
	file = {[Ding.2002] Adaptive dimension reduction for clustering high dimensional data.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Ding.2002] Adaptive dimension reduction for clustering high dimensional data.pdf:application/pdf}
}

@inproceedings{li_document_2004,
	title = {Document clustering via adaptive subspace iteration},
	booktitle = {Proceedings of the 27th annual international {ACM} {SIGIR} conference on {Research} and development in information retrieval},
	publisher = {ACM Press},
	author = {Li, Tao and Ma, Sheng and Ogihara, Mitsunori},
	year = {2004},
	pages = {218},
	file = {[Li.2004] Document clustering via adaptive subspace iteration.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Li.2004] Document clustering via adaptive subspace iteration.pdf:application/pdf}
}

@article{ma_review_2013,
	title = {A {Review} on {Dimension} {Reduction}: \textit{{A}} {Review} on {Dimension} {Reduction}},
	volume = {81},
	number = {1},
	journal = {International Statistical Review},
	author = {Ma, Yanyuan and Zhu, Liping},
	month = apr,
	year = {2013},
	pages = {134--150},
	file = {[Ma.2013] A Review on Dimension Reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Ma.2013] A Review on Dimension Reduction.pdf:application/pdf}
}

@article{min_locality_2004,
	title = {Locality pursuit embedding},
	volume = {37},
	number = {4},
	journal = {Pattern Recognition},
	author = {Min, Wanli and Lu, Ke and He, Xiaofei},
	month = apr,
	year = {2004},
	pages = {781--788},
	file = {[Min.2004] Locality pursuit embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Min.2004] Locality pursuit embedding.pdf:application/pdf}
}

@article{zheng_supervised_2006,
	title = {Supervised locality pursuit embedding for pattern classification},
	volume = {24},
	number = {8},
	journal = {Image and Vision Computing},
	author = {Zheng, Zhonglong and Yang, Jie},
	month = aug,
	year = {2006},
	pages = {819--826},
	file = {[Zheng.2006] Supervised locality pursuit embedding for pattern classification.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zheng.2006] Supervised locality pursuit embedding for pattern classification.pdf:application/pdf}
}

@article{lai_maximal_2011,
	title = {Maximal local interclass embedding with application to face recognition},
	volume = {22},
	number = {4},
	journal = {Machine Vision and Applications},
	author = {Lai, Zhihui and Zhao, Cairong and Chen, Yi and Jin, Zhong},
	month = jul,
	year = {2011},
	pages = {619--627},
	file = {[Lai.2011] Maximal local interclass embedding with application to face recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Lai.2011] Maximal local interclass embedding with application to face recognition.pdf:application/pdf}
}

@inproceedings{cai_learning_2007,
	title = {Learning a {Spatially} {Smooth} {Subspace} for {Face} {Recognition}},
	booktitle = {2007 {IEEE} {Conference} on {Computer} {Vision} and {Pattern} {Recognition}},
	publisher = {IEEE},
	author = {Cai, Deng and He, Xiaofei and Hu, Yuxiao and Han, Jiawei and Huang, Thomas},
	month = jun,
	year = {2007},
	pages = {1--7},
	file = {[Cai.2007] Learning a Spatially Smooth Subspace for Face Recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Cai.2007] Learning a Spatially Smooth Subspace for Face Recognition.pdf:application/pdf}
}

@article{raducanu_supervised_2012,
	title = {A supervised non-linear dimensionality reduction approach for manifold learning},
	volume = {45},
	number = {6},
	journal = {Pattern Recognition},
	author = {Raducanu, B. and Dornaika, F.},
	month = jun,
	year = {2012},
	pages = {2432--2444},
	file = {[Raducanu.2012] A supervised non-linear dimensionality reduction approach for manifold learning.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Raducanu.2012] A supervised non-linear dimensionality reduction approach for manifold learning.pdf:application/pdf}
}

@article{dornaika_enhanced_2013,
	title = {Enhanced and parameterless {Locality} {Preserving} {Projections} for face recognition},
	volume = {99},
	journal = {Neurocomputing},
	author = {Dornaika, Fadi and Assoum, Ammar},
	month = jan,
	year = {2013},
	pages = {448--457},
	file = {[Dornaika.2013] Enhanced and parameterless Locality Preserving Projections for face recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Dornaika.2013] Enhanced and parameterless Locality Preserving Projections for face recognition.pdf:application/pdf}
}

@article{yang_collaborative_2015,
	title = {A collaborative representation based projections method for feature extraction},
	volume = {48},
	number = {1},
	journal = {Pattern Recognition},
	author = {Yang, Wankou and Wang, Zhenyu and Sun, Changyin},
	month = jan,
	year = {2015},
	pages = {20--27},
	file = {[Yang.2015] A collaborative representation based projections method for feature extraction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Yang.2015] A collaborative representation based projections method for feature extraction.pdf:application/pdf}
}

@article{haixianwang_localitypreserved_2008,
	title = {Locality-{Preserved} {Maximum} {Information} {Projection}},
	volume = {19},
	number = {4},
	journal = {IEEE Transactions on Neural Networks},
	author = {{Haixian Wang} and {Sibao Chen} and {Zilan Hu} and {Wenming Zheng}},
	month = apr,
	year = {2008},
	pages = {571--585},
	file = {[Haixian Wang.2008] Locality-Preserved Maximum Information Projection.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Haixian Wang.2008] Locality-Preserved Maximum Information Projection.pdf:application/pdf}
}

@article{yang_locally_2006,
	title = {Locally principal component learning for face representation and recognition},
	volume = {69},
	number = {13-15},
	journal = {Neurocomputing},
	author = {Yang, Jian and Zhang, David and Yang, Jing-yu},
	month = aug,
	year = {2006},
	pages = {1697--1701},
	file = {[Yang.2006] Locally principal component learning for face representation and recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Yang.2006] Locally principal component learning for face representation and recognition.pdf:application/pdf}
}

@article{zhang_semisupervised_2011,
	title = {Semi-supervised locally discriminant projection for classification and recognition},
	volume = {24},
	number = {2},
	journal = {Knowledge-Based Systems},
	author = {Zhang, Shanwen and Lei, Ying-Ke and Wu, Yan-Hua},
	month = mar,
	year = {2011},
	pages = {341--346},
	file = {[Zhang.2011] Semi-supervised locally discriminant projection for classification and.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhang.2011] Semi-supervised locally discriminant projection for classification and.pdf:application/pdf}
}

@article{zhao_local_2006,
	title = {Local structure based supervised feature extraction},
	volume = {39},
	number = {8},
	journal = {Pattern Recognition},
	author = {Zhao, Haitao and Sun, Shaoyuan and Jing, Zhongliang and Yang, Jingyu},
	month = aug,
	year = {2006},
	pages = {1546--1550},
	file = {[Zhao.2006] Local structure based supervised feature extraction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhao.2006] Local structure based supervised feature extraction.pdf:application/pdf}
}

@article{zhao_locality_2008,
	title = {Locality sensitive semi-supervised feature selection},
	volume = {71},
	number = {10-12},
	journal = {Neurocomputing},
	author = {Zhao, Jidong and Lu, Ke and He, Xiaofei},
	month = jun,
	year = {2008},
	pages = {1842--1849},
	file = {[Zhao.2008] Locality sensitive semi-supervised feature selection.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhao.2008] Locality sensitive semi-supervised feature selection.pdf:application/pdf}
}

@inproceedings{he_laplacian_2005,
	address = {Cambridge, MA, USA},
	series = {{NIPS}'05},
	title = {Laplacian {Score} for {Feature} {Selection}},
	booktitle = {Proceedings of the 18th {International} {Conference} on {Neural} {Information} {Processing} {Systems}},
	publisher = {MIT Press},
	author = {He, Xiaofei and Cai, Deng and Niyogi, Partha},
	year = {2005},
	pages = {507--514},
	file = {[He.2005] Laplacian Score for Feature Selection.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[He.2005] Laplacian Score for Feature Selection.pdf:application/pdf}
}

@article{valizadehasanloei_combined_2018,
	title = {A combined {Fisher} and {Laplacian} score for feature selection in {QSAR} based drug design using compounds with known and unknown activities},
	volume = {32},
	doi = {10.1007/s10822-017-0094-6},
	number = {2},
	journal = {Journal of Computer-Aided Molecular Design},
	author = {Valizade Hasanloei, Mohammad Amin and Sheikhpour, Razieh and Sarram, Mehdi Agha and Sheikhpour, Elnaz and Sharifi, Hamdollah},
	month = feb,
	year = {2018},
	pages = {375--384},
	file = {[Valizade Hasanloei.2018] A combined Fisher and Laplacian score for feature selection in QSAR based drug.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Valizade Hasanloei.2018] A combined Fisher and Laplacian score for feature selection in QSAR based drug.pdf:application/pdf}
}

@inproceedings{cai_unsupervised_2010,
	title = {Unsupervised feature selection for multi-cluster data},
	booktitle = {Proceedings of the 16th {ACM} {SIGKDD} international conference on {Knowledge} discovery and data mining},
	publisher = {ACM Press},
	author = {Cai, Deng and Zhang, Chiyuan and He, Xiaofei},
	year = {2010},
	pages = {333--342},
	file = {[Cai.2010] Unsupervised feature selection for multi-cluster data.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Cai.2010] Unsupervised feature selection for multi-cluster data.pdf:application/pdf}
}

@article{jin_face_2001,
	title = {Face recognition based on the uncorrelated discriminant transformation},
	volume = {34},
	number = {7},
	journal = {Pattern Recognition},
	author = {Jin, Zhong and Yang, Jing-Yu and Hu, Zhong-Shan and Lou, Zhen},
	year = {2001},
	keywords = {Feature extraction, Pattern recognition, Dimensionality reduction, Discriminant analysis, Face recognition},
	pages = {1405 -- 1416},
	file = {[Jin.2001] Face recognition based on the uncorrelated discriminant transformation.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Jin.2001] Face recognition based on the uncorrelated discriminant transformation.pdf:application/pdf}
}

@article{ye_characterization_2005,
	title = {Characterization of a {Family} of {Algorithms} for {Generalized} {Discriminant} {Analysis} on {Undersampled} {Problems}},
	volume = {6},
	issn = {1532-4435},
	journal = {J. Mach. Learn. Res.},
	author = {Ye, Jieping},
	month = dec,
	year = {2005},
	pages = {483--502},
	file = {[Ye.2005] Characterization of a Family of Algorithms for Generalized Discriminant.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Ye.2005] Characterization of a Family of Algorithms for Generalized Discriminant.pdf:application/pdf}
}

@article{kokiopoulou_orthogonal_2007,
	title = {Orthogonal {Neighborhood} {Preserving} {Projections}: {A} {Projection}-{Based} {Dimensionality} {Reduction} {Technique}},
	volume = {29},
	number = {12},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	author = {Kokiopoulou, E. and Saad, Y.},
	month = dec,
	year = {2007},
	pages = {2143--2156},
	file = {[Kokiopoulou.2007] Orthogonal Neighborhood Preserving Projections.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Kokiopoulou.2007] Orthogonal Neighborhood Preserving Projections.pdf:application/pdf}
}

@article{tianhaozhang_discriminative_2010,
	title = {Discriminative {Orthogonal} {Neighborhood}-{Preserving} {Projections} for {Classification}},
	volume = {40},
	number = {1},
	journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
	author = {{Tianhao Zhang} and {Kaiqi Huang} and {Xuelong Li} and {Jie Yang} and {Dacheng Tao}},
	month = feb,
	year = {2010},
	pages = {253--263},
	file = {[Tianhao Zhang.2010] Discriminative Orthogonal Neighborhood-Preserving Projections for Classification.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Tianhao Zhang.2010] Discriminative Orthogonal Neighborhood-Preserving Projections for Classification.pdf:application/pdf}
}

@inproceedings{zafeiriou_nonnegative_2010,
	title = {Nonnegative {Embeddings} and {Projections} for {Dimensionality} {Reduction} and {Information} {Visualization}},
	booktitle = {2010 20th {International} {Conference} on {Pattern} {Recognition}},
	publisher = {IEEE},
	author = {Zafeiriou, Stefanos and Laskaris, Nikolaos},
	month = aug,
	year = {2010},
	pages = {726--729},
	file = {[Zafeiriou.2010] Nonnegative Embeddings and Projections for Dimensionality Reduction and.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zafeiriou.2010] Nonnegative Embeddings and Projections for Dimensionality Reduction and.pdf:application/pdf}
}

@article{song_face_2007,
	title = {Face recognition based on a novel linear discriminant criterion},
	volume = {10},
	number = {3},
	journal = {Pattern Analysis and Applications},
	author = {Song, Fengxi and Zhang, David and Chen, Qinglong and Wang, Jizhong},
	month = jul,
	year = {2007},
	pages = {165--174},
	file = {[Song.2007] Face recognition based on a novel linear discriminant criterion.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Song.2007] Face recognition based on a novel linear discriminant criterion.pdf:application/pdf}
}

@article{fengxisong_multiple_2007,
	title = {A {Multiple} {Maximum} {Scatter} {Difference} {Discriminant} {Criterion} for {Facial} {Feature} {Extraction}},
	volume = {37},
	number = {6},
	journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
	author = {{Fengxi Song} and Zhang, D. and {Dayong Mei} and {Zhongwei Guo}},
	month = dec,
	year = {2007},
	pages = {1599--1606},
	file = {[Fengxi Song.2007] A Multiple Maximum Scatter Difference Discriminant Criterion for Facial Feature.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Fengxi Song.2007] A Multiple Maximum Scatter Difference Discriminant Criterion for Facial Feature.pdf:application/pdf}
}

@inproceedings{zhao_locality_2009,
	address = {Berlin, Heidelberg},
	title = {Locality {Preserving} {Fisher} {Discriminant} {Analysis} for {Face} {Recognition}},
	booktitle = {Emerging {Intelligent} {Computing} {Technology} and {Applications}},
	publisher = {Springer Berlin Heidelberg},
	author = {Zhao, Xu and Tian, Xiaoyan},
	editor = {Huang, De-Shuang and Jo, Kang-Hyun and Lee, Hong-Hee and Kang, Hee-Jun and Bevilacqua, Vitoantonio},
	year = {2009},
	pages = {261--269},
	file = {[Zhao.2009] Locality Preserving Fisher Discriminant Analysis for Face Recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhao.2009] Locality Preserving Fisher Discriminant Analysis for Face Recognition.pdf:application/pdf}
}

@article{wiskott_slow_2002,
	title = {Slow {Feature} {Analysis}: {Unsupervised} {Learning} of {Invariances}},
	volume = {14},
	number = {4},
	journal = {Neural Computation},
	author = {Wiskott, Laurenz and Sejnowski, Terrence J.},
	month = apr,
	year = {2002},
	pages = {715--770},
	file = {[Wiskott.2002] Slow Feature Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Wiskott.2002] Slow Feature Analysis.pdf:application/pdf}
}

@article{sprekeler_understanding_2008,
	title = {Understanding {Slow} {Feature} {Analysis}: {A} {Mathematical} {Framework}},
	journal = {SSRN Electronic Journal},
	author = {Sprekeler, Henning and Wiskott, Laurenz},
	year = {2008},
	file = {[Sprekeler.2008] Understanding Slow Feature Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Sprekeler.2008] Understanding Slow Feature Analysis.pdf:application/pdf}
}

@article{kompella_incremental_2012,
	title = {Incremental {Slow} {Feature} {Analysis}: {Adaptive} {Low}-{Complexity} {Slow} {Feature} {Updating} from {High}-{Dimensional} {Input} {Streams}},
	volume = {24},
	number = {11},
	journal = {Neural Computation},
	author = {Kompella, Varun Raj and Luciw, Matthew and Schmidhuber, Jürgen},
	month = nov,
	year = {2012},
	pages = {2994--3024},
	file = {[Kompella.2012] Incremental Slow Feature Analysis.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Kompella.2012] Incremental Slow Feature Analysis.pdf:application/pdf}
}

@article{miao_manifold_2017,
	title = {Manifold {Regularized} {Slow} {Feature} {Analysis} for {Dynamic} {Texture} {Recognition}},
	journal = {ArXiv e-prints},
	author = {Miao, J. and Xu, X. and Xing, X. and Tao, D.},
	month = jun,
	year = {2017},
	keywords = {Computer Science - Computer Vision and Pattern Recognition},
	file = {[Miao.2017] Manifold Regularized Slow Feature Analysis for Dynamic Texture Recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Miao.2017] Manifold Regularized Slow Feature Analysis for Dynamic Texture Recognition.pdf:application/pdf}
}

@article{tianhaozhang_patch_2009,
	title = {Patch {Alignment} for {Dimensionality} {Reduction}},
	volume = {21},
	number = {9},
	journal = {IEEE Transactions on Knowledge and Data Engineering},
	author = {{Tianhao Zhang} and {Dacheng Tao} and {Xuelong Li} and {Jie Yang}},
	month = sep,
	year = {2009},
	pages = {1299--1313},
	file = {[Tianhao Zhang.2009] Patch Alignment for Dimensionality Reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Tianhao Zhang.2009] Patch Alignment for Dimensionality Reduction.pdf:application/pdf}
}

@article{wang_combining_2009,
	title = {Combining local and global information for nonlinear dimensionality reduction},
	volume = {72},
	number = {10-12},
	journal = {Neurocomputing},
	author = {Wang, Qinggang and Li, Jianwei},
	month = jun,
	year = {2009},
	pages = {2235--2241},
	file = {[Wang.2009] Combining local and global information for nonlinear dimensionality reduction.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Wang.2009] Combining local and global information for nonlinear dimensionality reduction.pdf:application/pdf}
}

@article{cao_regularized_2012,
	title = {On the regularized {Laplacian} eigenmaps},
	volume = {142},
	number = {7},
	journal = {Journal of Statistical Planning and Inference},
	author = {Cao, Ying and Chen, Di-Rong},
	month = jul,
	year = {2012},
	pages = {1627--1643},
	file = {[Cao.2012] On the regularized Laplacian eigenmaps.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Cao.2012] On the regularized Laplacian eigenmaps.pdf:application/pdf}
}

@article{qinggang_distinguishing_2010,
	title = {Distinguishing variance embedding},
	volume = {28},
	number = {6},
	journal = {Image and Vision Computing},
	author = {Qinggang, Wang and Jianwei, Li and Xuchu, Wang},
	month = jun,
	year = {2010},
	pages = {872--880},
	file = {[Qinggang.2010] Distinguishing variance embedding.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Qinggang.2010] Distinguishing variance embedding.pdf:application/pdf}
}

@article{dornaika_exponential_2013,
	title = {Exponential {Local} {Discriminant} {Embedding} and {Its} {Application} to {Face} {Recognition}},
	volume = {43},
	number = {3},
	journal = {IEEE Transactions on Cybernetics},
	author = {Dornaika, F. and Bosaghzadeh, A.},
	month = jun,
	year = {2013},
	pages = {921--934},
	file = {[Dornaika.2013] Exponential Local Discriminant Embedding and Its Application to Face Recognition.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Dornaika.2013] Exponential Local Discriminant Embedding and Its Application to Face Recognition.pdf:application/pdf}
}

@inproceedings{lu_adaptive_2011,
	title = {Adaptive maximum margin criterion for image classification},
	booktitle = {2011 {IEEE} {International} {Conference} on {Multimedia} and {Expo}},
	publisher = {IEEE},
	author = {Lu, Jiwen and Tan, Yap-Peng},
	month = jul,
	year = {2011},
	pages = {1--6},
	file = {[Lu.2011] Adaptive maximum margin criterion for image classification.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Lu.2011] Adaptive maximum margin criterion for image classification.pdf:application/pdf}
}

@article{zhang_improved_2011,
	title = {An improved local tangent space alignment method for manifold learning},
	volume = {32},
	number = {2},
	journal = {Pattern Recognition Letters},
	author = {Zhang, Peng and Qiao, Hong and Zhang, Bo},
	month = jan,
	year = {2011},
	pages = {181--189},
	file = {[Zhang.2011] An improved local tangent space alignment method for manifold learning.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhang.2011] An improved local tangent space alignment method for manifold learning.pdf:application/pdf}
}

@article{zhang_graphoptimized_2010,
	title = {Graph-optimized locality preserving projections},
	volume = {43},
	number = {6},
	journal = {Pattern Recognition},
	author = {Zhang, Limei and Qiao, Lishan and Chen, Songcan},
	month = jun,
	year = {2010},
	pages = {1993--2002},
	file = {[Zhang.2010] Graph-optimized locality preserving projections.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zhang.2010] Graph-optimized locality preserving projections.pdf:application/pdf}
}

@article{bouzas_graph_2015,
	title = {Graph {Embedded} {Nonparametric} {Mutual} {Information} for {Supervised} {Dimensionality} {Reduction}},
	volume = {26},
	number = {5},
	journal = {IEEE Transactions on Neural Networks and Learning Systems},
	author = {Bouzas, Dimitrios and Arvanitopoulos, Nikolaos and Tefas, Anastasios},
	month = may,
	year = {2015},
	pages = {951--963},
	file = {[Bouzas.2015] Graph Embedded Nonparametric Mutual Information for Supervised Dimensionality.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Bouzas.2015] Graph Embedded Nonparametric Mutual Information for Supervised Dimensionality.pdf:application/pdf}
}

@article{ma_alternating_2013,
	title = {Alternating {Direction} {Method} of {Multipliers} for {Sparse} {Principal} {Component} {Analysis}},
	volume = {1},
	number = {2},
	journal = {Journal of the Operations Research Society of China},
	author = {Ma, Shiqian},
	month = jun,
	year = {2013},
	pages = {253--274},
	file = {[Ma.2013] Alternating Direction Method of Multipliers for Sparse Principal Component.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Ma.2013] Alternating Direction Method of Multipliers for Sparse Principal Component.pdf:application/pdf}
}

@article{hentschel_infinite_1983,
	title = {The infinite number of generalized dimensions of fractals and strange attractors},
	volume = {8},
	number = {3},
	journal = {Physica D: Nonlinear Phenomena},
	author = {Hentschel, H.G.E. and Procaccia, Itamar},
	month = sep,
	year = {1983},
	pages = {435--444}
}

@inproceedings{hein_intrinsic_2005a,
	title = {Intrinsic dimensionality estimation of submanifolds in {R} $^{\textrm{d}}$\$},
	booktitle = {Proceedings of the 22nd international conference on {Machine} learning},
	publisher = {ACM Press},
	author = {Hein, Matthias and Audibert, Jean-Yves},
	year = {2005},
	pages = {289--296}
}

@inproceedings{he_graph_2009,
	title = {Graph {Embedding} with {Constraints}},
	booktitle = {{IJCAI}},
	author = {He, Xiaofei and Ji, Ming and Bao, Hujun},
	year = {2009}
}

@article{dy_feature_2004,
	title = {Feature {Selection} for {Unsupervised} {Learning}},
	volume = {5},
	journal = {J. Mach. Learn. Res.},
	author = {Dy, Jennifer G. and Brodley, Carla E.},
	month = dec,
	year = {2004},
	pages = {845--889}
}

@incollection{mcqueen_nearly_2016,
	title = {Nearly {Isometric} {Embedding} by {Relaxation}},
	url = {http://papers.nips.cc/paper/6535-nearly-isometric-embedding-by-relaxation.pdf},
	booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 29},
	publisher = {Curran Associates, Inc.},
	author = {McQueen, James and Meila, Marina and Joncas, Dominique},
	editor = {Lee, D. D. and Sugiyama, M. and Luxburg, U. V. and Guyon, I. and Garnett, R.},
	year = {2016},
	pages = {2631--2639},
	file = {[McQueen.2016] Nearly Isometric Embedding by Relaxation.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[McQueen.2016] Nearly Isometric Embedding by Relaxation.pdf:application/pdf}
}

@incollection{lombardi_minimum_2011,
	address = {Berlin, Heidelberg},
	title = {Minimum {Neighbor} {Distance} {Estimators} of {Intrinsic} {Dimension}},
	volume = {6912},
	isbn = {978-3-642-23782-9 978-3-642-23783-6},
	booktitle = {Machine {Learning} and {Knowledge} {Discovery} in {Databases}},
	publisher = {Springer Berlin Heidelberg},
	author = {Lombardi, Gabriele and Rozza, Alessandro and Ceruti, Claudio and Casiraghi, Elena and Campadelli, Paola},
	editor = {Gunopulos, Dimitrios and Hofmann, Thomas and Malerba, Donato and Vazirgiannis, Michalis},
	year = {2011},
	doi = {10.1007/978-3-642-23783-6_24},
	pages = {374--389},
	file = {[Lombardi.2011] Minimum Neighbor Distance Estimators of Intrinsic Dimension.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Lombardi.2011] Minimum Neighbor Distance Estimators of Intrinsic Dimension.pdf:application/pdf}
}

@article{he_intrinsic_2014,
	title = {Intrinsic dimensionality estimation based on manifold assumption},
	volume = {25},
	number = {5},
	journal = {Journal of Visual Communication and Image Representation},
	author = {He, Jinrong and Ding, Lixin and Jiang, Lei and Li, Zhaokui and Hu, Qinghui},
	month = jul,
	year = {2014},
	pages = {740--747}
}

@article{ceruti_danco_2014,
	title = {{DANCo}: {An} intrinsic dimensionality estimator exploiting angle and norm concentration},
	volume = {47},
	number = {8},
	journal = {Pattern Recognition},
	author = {Ceruti, Claudio and Bassis, Simone and Rozza, Alessandro and Lombardi, Gabriele and Casiraghi, Elena and Campadelli, Paola},
	month = aug,
	year = {2014},
	pages = {2569--2581}
}

@article{erba_intrinsic_2019,
	title = {Intrinsic dimension estimation for locally undersampled data},
	volume = {9},
	number = {1},
	journal = {Scientific Reports},
	author = {Erba, Vittorio and Gherardi, Marco and Rotondo, Pietro},
	month = dec,
	year = {2019},
	file = {[Erba.2019] Intrinsic dimension estimation for locally undersampled data.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Erba.2019] Intrinsic dimension estimation for locally undersampled data.pdf:application/pdf}
}

@inproceedings{costa_estimating_2005,
	address = {Bordeaux, France},
	title = {Estimating {Local} {Intrinsic} {Dimension} with k-{Nearest} {Neighbor} {Graphs}},
	booktitle = {{IEEE}/{SP} 13th {Workshop} on {Statistical} {Signal} {Processing}, 2005},
	publisher = {IEEE},
	author = {Costa, J.A. and Girotra, A. and Hero, A.O.},
	year = {2005},
	pages = {417--422}
}

@article{carter_local_2010,
	title = {On {Local} {Intrinsic} {Dimension} {Estimation} and {Its} {Applications}},
	volume = {58},
	number = {2},
	journal = {IEEE Transactions on Signal Processing},
	author = {Carter, K.M. and Raich, R. and Hero, A.O.},
	month = feb,
	year = {2010},
	pages = {650--663},
	file = {[Carter.2010] On Local Intrinsic Dimension Estimation and Its Applications.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Carter.2010] On Local Intrinsic Dimension Estimation and Its Applications.pdf:application/pdf}
}

@article{minsker_geometric_2015,
	title = {Geometric median and robust estimation in {Banach} spaces},
	volume = {21},
	number = {4},
	journal = {Bernoulli},
	author = {Minsker, Stanislav},
	month = nov,
	year = {2015},
	pages = {2308--2335},
	file = {[Minsker.2015] Geometric median and robust estimation in Banach spaces.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Minsker.2015] Geometric median and robust estimation in Banach spaces.pdf:application/pdf}
}

@article{oh_bayesian_2001,
	title = {Bayesian {Multidimensional} {Scaling} and {Choice} of {Dimension}},
	volume = {96},
	number = {455},
	journal = {Journal of the American Statistical Association},
	author = {Oh, Man-Suk and Raftery, Adrian E},
	month = sep,
	year = {2001},
	pages = {1031--1044}
}

@article{zhang_constraint_2008a,
	title = {Constraint {Score}: {A} new filter method for feature selection with pairwise constraints},
	volume = {41},
	number = {5},
	journal = {Pattern Recognition},
	author = {Zhang, Daoqiang and Chen, Songcan and Zhou, Zhi-Hua},
	month = may,
	year = {2008},
	pages = {1440--1451}
}

@inproceedings{zhao_spectral_2007,
	address = {Corvalis, Oregon},
	title = {Spectral feature selection for supervised and unsupervised learning},
	booktitle = {Proceedings of the 24th international conference on {Machine} learning - {ICML} '07},
	publisher = {ACM Press},
	author = {Zhao, Zheng and Liu, Huan},
	year = {2007},
	pages = {1151--1157}
}

@article{zou_regularization_2005,
	title = {Regularization and variable selection via the elastic net},
	volume = {67},
	number = {2},
	journal = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
	author = {Zou, Hui and Hastie, Trevor},
	month = apr,
	year = {2005},
	pages = {301--320},
	file = {[Zou.2005] Regularization and variable selection via the elastic net.pdf:/home/kisung/Dropbox/VP. Packages/Rdimtools/[Zou.2005] Regularization and variable selection via the elastic net.pdf:application/pdf}
}

@article{tibshirani_regression_1996,
	title = {Regression shrinkage and selection via the lasso},
	volume = {58},
	number = {1},
	journal = {Journal of the Royal Statistical Society. Series B (Methodological)},
	author = {Tibshirani, Robert},
	year = {1996},
	note = {tex.publisher: [Royal Statistical Society, Wiley]},
	pages = {267--288}
}