low-rank approximation

Matrix Completion with Noisy Side Information NeurIPS 2015 On the Complexity of Learning with Kernels COLT 2015 Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition NeurIPS 2015 Relaxing From Vocabulary: Robust Weakly-Supervised Deep Learning for Vocabulary-Free Image Tagging ICCV 2015 Robust sketching for multiple square-root LASSO problems AISTATS 2015 Simultaneous Pursuit of Sparseness and Rank Structures for Matrix Decomposition JMLR 2015 Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nyström Method AISTATS 2015 Supervised Descriptor Learning for Multi-Output Regression CVPR 2015 Tensorizing Neural Networks NeurIPS 2015 The Algebraic Combinatorial Approach for Low-Rank Matrix Completion JMLR 2015 Adaptive Object Retrieval with Kernel Reconstructive Hashing CVPR 2014 Curvilinear Structure Tracking by Low Rank Tensor Approximation with Model Propagation CVPR 2014 Decomposable Nonlocal Tensor Dictionary Learning for Multispectral Image Denoising CVPR 2014 Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning NeurIPS 2014 Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion NeurIPS 2014 Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction NeurIPS 2014 Improved Distributed Principal Component Analysis NeurIPS 2014 Large-scale Multi-label Learning with Missing Labels ICML 2014 Low Rank Approximation Lower Bounds in Row-Update Streams NeurIPS 2014 Low-Rank Spectral Learning AISTATS 2014 Matrix Completion with the Trace Norm: Learning, Bounding, and Transducing JMLR 2014 Memory Efficient Kernel Approximation ICML 2014 Prediction and Clustering in Signed Networks: A Local to Global Perspective JMLR 2014 Principal Component Analysis and Higher Correlations for Distributed Data COLT 2014 Subspace Embeddings for the Polynomial Kernel NeurIPS 2014