Online Learning in the Embedded Manifold of Low-rank Matrices
暂无分享,去创建一个
[1] Tomer Hertz,et al. Learning a Mahalanobis Metric from Equivalence Constraints , 2005, J. Mach. Learn. Res..
[2] Jérôme Malick,et al. Projection-like Retractions on Matrix Manifolds , 2012, SIAM J. Optim..
[3] Inderjit S. Dhillon,et al. Online Metric Learning and Fast Similarity Search , 2008, NIPS.
[4] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[5] Liu Yang. An Overview of Distance Metric Learning , 2007 .
[6] Stefan Vandewalle,et al. A Riemannian Optimization Approach for Computing Low-Rank Solutions of Lyapunov Equations , 2010, SIAM J. Matrix Anal. Appl..
[7] Ambuj Tewari,et al. Regularization Techniques for Learning with Matrices , 2009, J. Mach. Learn. Res..
[8] Sabine Van Huffel,et al. Best Low Multilinear Rank Approximation of Higher-Order Tensors, Based on the Riemannian Trust-Region Scheme , 2011, SIAM J. Matrix Anal. Appl..
[9] Andrea Montanari,et al. Matrix Completion from Noisy Entries , 2009, J. Mach. Learn. Res..
[10] Yanjun Qi,et al. Supervised semantic indexing , 2009, ECIR.
[11] Inderjit S. Dhillon,et al. Rank minimization via online learning , 2008, ICML '08.
[12] I. Holopainen. Riemannian Geometry , 1927, Nature.
[13] Martin J. Wainwright,et al. Estimation of (near) low-rank matrices with noise and high-dimensional scaling , 2009, ICML.
[14] Koby Crammer,et al. Online Passive-Aggressive Algorithms , 2003, J. Mach. Learn. Res..
[15] Kilian Q. Weinberger,et al. Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.
[16] Fei-Fei Li,et al. Hierarchical semantic indexing for large scale image retrieval , 2011, CVPR 2011.
[17] Samy Bengio,et al. Large Scale Online Learning of Image Similarity Through Ranking , 2009, J. Mach. Learn. Res..
[18] Levent Tunçel,et al. Optimization algorithms on matrix manifolds , 2009, Math. Comput..
[19] Michael I. Jordan,et al. Distance Metric Learning with Application to Clustering with Side-Information , 2002, NIPS.
[20] Pablo A. Parrilo,et al. Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization , 2007, SIAM Rev..
[21] Inderjit S. Dhillon,et al. Low-Rank Kernel Learning with Bregman Matrix Divergences , 2009, J. Mach. Learn. Res..
[22] Samy Bengio,et al. A Discriminative Kernel-Based Approach to Rank Images from Text Queries , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Yiming Yang,et al. A Comparative Study on Feature Selection in Text Categorization , 1997, ICML.
[24] Ken Lang,et al. NewsWeeder: Learning to Filter Netnews , 1995, ICML.
[25] Berkant Savas,et al. A Newton-Grassmann Method for Computing the Best Multilinear Rank-(r1, r2, r3) Approximation of a Tensor , 2009, SIAM J. Matrix Anal. Appl..
[26] Jason Weston,et al. WSABIE: Scaling Up to Large Vocabulary Image Annotation , 2011, IJCAI.
[27] Yurii Nesterov,et al. Generalized Power Method for Sparse Principal Component Analysis , 2008, J. Mach. Learn. Res..
[28] J. Meyer. Generalized Inversion of Modified Matrices , 1973 .
[29] Bart Vandereycken,et al. Embedded geometry of the set of symmetric positive semidefinite matrices of fixed rank , 2009, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing.
[30] Daphna Weinshall,et al. Online Learning in The Manifold of Low-Rank Matrices , 2010, NIPS.
[31] Stephen J. Wright,et al. Active Set Identification in Nonlinear Programming , 2006, SIAM J. Optim..
[32] Geoffrey E. Hinton,et al. Neighbourhood Components Analysis , 2004, NIPS.
[33] Balas K. Natarajan,et al. Sparse Approximate Solutions to Linear Systems , 1995, SIAM J. Comput..
[34] Frank Vallentin,et al. The Grothendieck problem with rank constraint , 2010 .
[35] Yoram Singer,et al. Online and batch learning of pseudo-metrics , 2004, ICML.
[36] David Grangier,et al. A Discriminative Kernel-based Model to Rank Images from Text Queries , 2007 .
[37] Stephen P. Boyd,et al. Rank minimization and applications in system theory , 2004, Proceedings of the 2004 American Control Conference.
[38] Kaare Brandt Petersen,et al. The Matrix Cookbook , 2006 .
[39] Inderjit S. Dhillon,et al. Guaranteed Rank Minimization via Singular Value Projection , 2009, NIPS.
[40] Francis R. Bach,et al. Low-Rank Optimization on the Cone of Positive Semidefinite Matrices , 2008, SIAM J. Optim..
[41] Silvere Bonnabel,et al. Regression on Fixed-Rank Positive Semidefinite Matrices: A Riemannian Approach , 2010, J. Mach. Learn. Res..
[42] Amir Globerson,et al. Metric Learning by Collapsing Classes , 2005, NIPS.