matrix decomposition

Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices NeurIPS 2014 Efficient Higher-Order Clustering on the Grassmann Manifold ICCV 2013 Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA NeurIPS 2013 Improving CUR Matrix Decomposition and the Nystrom Approximation via Adaptive Sampling JMLR 2013 Learning Multi-level Sparse Representations NeurIPS 2013 On Algorithms for Sparse Multi-factor NMF NeurIPS 2013 Online Robust PCA via Stochastic Optimization NeurIPS 2013 Spectral Learning of Hidden Markov Models from Dynamic and Static Data ICML 2013 The CAM Software for Nonnegative Blind Source Separation in R-Java JMLR 2013 Uncalibrated Photometric Stereo for Unknown Isotropic Reflectances CVPR 2013 Unifying Nuclear Norm and Bilinear Factorization Approaches for Low-Rank Matrix Decomposition ICCV 2013 A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound NeurIPS 2012 Joint Modeling of a Matrix with Associated Text via Latent Binary Features NeurIPS 2012 Near-Optimal Algorithms for Online Matrix Prediction COLT 2012 NIMFA : A Python Library for Nonnegative Matrix Factorization JMLR 2012 Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NeurIPS 2012 Spectral Clustering of Graphs with General Degrees in the Extended Planted Partition Model COLT 2012 Minimax Localization of Structural Information in Large Noisy Matrices NeurIPS 2011 CUR from a Sparse Optimization Viewpoint NeurIPS 2010 Robust PCA via Outlier Pursuit NeurIPS 2010 Linearly constrained Bayesian matrix factorization for blind source separation NeurIPS 2009 Probabilistic Matrix Factorization NeurIPS 2007 Modeling Dyadic Data with Binary Latent Factors NeurIPS 2006 Towards a general independent subspace analysis NeurIPS 2006 On the Nystrom Method for Approximating a Gram Matrix for Improved Kernel-Based Learning JMLR 2005