low-rank approximation

Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach AISTATS 2012 A novel greedy algorithm for Nyström approximation AISTATS 2011 Can matrix coherence be efficiently and accurately estimated? AISTATS 2011 Information Theoretical Clustering via Semidefinite Programming AISTATS 2011 Learning with the weighted trace-norm under arbitrary sampling distributions NeurIPS 2011 Penalty Decomposition Methods for Rank Minimization NeurIPS 2011 Theoretical Analysis of Bayesian Matrix Factorization JMLR 2011 CUR from a Sparse Optimization Viewpoint NeurIPS 2010 Exploiting Feature Covariance in High-Dimensional Online Learning AISTATS 2010 Fluid Dynamics Models for Low Rank Discriminant Analysis AISTATS 2010 Large-Scale Matrix Factorization with Missing Data under Additional Constraints NeurIPS 2010 Robust PCA via Outlier Pursuit NeurIPS 2010 Spectral Regularization Algorithms for Learning Large Incomplete Matrices JMLR 2010 Transduction with Matrix Completion: Three Birds with One Stone NeurIPS 2010 Ensemble Nystrom Method NeurIPS 2009 Polynomial Semantic Indexing NeurIPS 2009 Graph Laplacian Regularization for Large-Scale Semidefinite Programming NeurIPS 2006 On the Nystrom Method for Approximating a Gram Matrix for Improved Kernel-Based Learning JMLR 2005 Efficient SVM Training Using Low-Rank Kernel Representations JMLR 2001