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This is a detailed tutorial paper which explains the Fisher discriminant Analysis (FDA) and kernel FDA.
Eigenvalue and generalized eigenvalue problems: Tutorial
Ghojogh, Benyamin, Karray, Fakhri, and Crowley, Mark · 1903
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The theory behind overfitting, cross validation, regularization, bagging, and boosting: Tutorial
Ghojogh, Benyamin and Crowley, Mark · 1905
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Feature selection and feature extraction in pattern analysis: A literature review
Ghojogh, Benyamin, Samad, Maria N, Mashhadi, Sayema Asif, Kapoor, Tania, Ali, Wahab, Karray, Fakhri, and Crowley, Mark · 1905
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Linear and quadratic discriminant analysis: Tutorial
Ghojogh, Benyamin and Crowley, Mark · 1906
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Unsupervised and supervised principal component analysis: Tutorial
Ghojogh, Benyamin and Crowley, Mark · 1906
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Xv.—the correlation between relatives on the supposition of mendelian inheritance
Fisher, Ronald A · 1919
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The use of multiple measurements in taxonomic problems
Fisher, Ronald A · 1936
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Face recognition using eigenfaces
Turk, Matthew A and Pentland, Alex P · 1991
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Statistical methods for research workers
Fisher, Ronald Aylmer · 1992
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Local representation theory: Modular representations as an introduction to the local representation theory of finite groups , volume 11
Alperin, Jonathan L · 1993
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Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection
Belhumeur, Peter N, Hespanha, João P, and Kriegman, David J · 1997
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Discriminant analysis for recognition of human face images
Etemad, Kamran and Chellappa, Rama · 1997
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The symmetric eigenvalue problem
Parlett, Beresford N · 1998
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Mahalanobis distance
McLachlan, Goeffrey J · 1999
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Fisher discriminant analysis with kernels
Mika, Sebastian, Rätsch, Gunnar, Weston, Jason, Schölkopf, Bernhard, and Müller, Klaus-Robert · 1999
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Subspace linear discriminant analysis for face recognition
Zhao, Wenyi, Chellappa, Rama, and Phillips, P Jonathon · 1999
Cited alongside, same era.
The Mahalanobis distance
De Maesschalck, Roy, Jouan-Rimbaud, Delphine, and Massart, Désiré L · 2000
Cited alongside, same era.
Invariant feature extraction and classification in kernel spaces
Mika, Sebastian, Rätsch, Gunnar, Weston, Jason, Schölkopf, Bernhard, Smola, Alex J, and Müller, Klaus-Robert · 2000
Cited alongside, same era.
Face recognition using kernel eigenfaces
Yang, M-H, Ahuja, Narendra, and Kriegman, David · 2000
Cited alongside, same era.
Learning kernel classifiers: theory and algorithms
Herbrich, Ralf · 2001
Cited alongside, same era.
Kernel Eigenfaces vs. kernel Fisherfaces: Face recognition using kernel methods
Yang, Ming-Hsuan · 2002
Cited alongside, same era.
Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis
Sugiyama, Masashi · 2007
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Distance metric learning vs. Fisher discriminant analysis
Alipanahi, Babak, Biggs, Michael, and Ghodsi, Ali · 2008
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Kernel methods in machine learning
Hofmann, Thomas, Schölkopf, Bernhard, and Smola, Alexander J · 2008
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The elements of statistical learning , volume 2
Friedman, Jerome, Hastie, Trevor, and Tibshirani, Robert · 2009
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Ensemble learning
Polikar, Robi · 2012
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Metric learning: A survey
Kulis, Brian et al · 2013
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Convex optimization
Boyd, Stephen and Vandenberghe, Lieven · 2004
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Science from Fisher information: a unification
Frieden, B Roy · 2004
Cited alongside, same era.
Improving kernel Fisher discriminant analysis for face recognition
Liu, Qingshan, Lu, Hanqing, and Ma, Songde · 2004
Cited alongside, same era.
Improved learning of Riemannian metrics for exploratory analysis
Peltonen, Jaakko, Klami, Arto, and Kaski, Samuel · 2004
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Fisher linear discriminant analysis
Welling, Max · 2005
Cited alongside, same era.
Metric learning by collapsing classes
Globerson, Amir and Roweis, Sam T · 2006
Cited alongside, same era.
Samadani, Ali-Akbar, Ghodsi, Ali, and Kulić, Dana · 2013
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A feature extraction method for human action recognition using body-worn inertial sensors
Guo, Ming and Wang, Zhelong · 2015
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Automatic extraction of key-poses and key-joints for action recognition using 3d skeleton data
Ghojogh, Benyamin and Mohammadzade, Hoda · 2017
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Fisherposes for human action recognition using kinect sensor data
Ghojogh, Benyamin, Mohammadzade, Hoda, and Mokari, Mozhgan · 2017
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Recognizing involuntary actions from 3d skeleton data using body states
Mokari, Mozhgan, Mohammadzade, Hoda, and Ghojogh, Benyamin · 2018
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The Rayleigh principle for finding eigenvalues
Croot, Ernie · 2019
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Classification course, department of statistics and actuarial science, university of Waterloo
Ghodsi, Ali · 2019
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Data visualization course, department of statistics and actuarial science, university of Waterloo
Ghodsi, Ali · 2019
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Generalized eigenvalue problem
Wang, Ruye · 2019
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