matrix approximation

Sublinear Time Approximation of Text Similarity Matrices AAAI 2022 Additive Error Guarantees for Weighted Low Rank Approximation ICML 2021 Analysis of stochastic Lanczos quadrature for spectrum approximation ICML 2021 Few-Shot Data-Driven Algorithms for Low Rank Approximation NeurIPS 2021 Heuristic Search for Approximating One Matrix in Terms of Another Matrix IJCAI 2021 Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract) IJCAI 2021 Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions JMLR 2021 Streaming and Distributed Algorithms for Robust Column Subset Selection ICML 2021 The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood COLT 2021 A determinantal point process for column subset selection JMLR 2020 Error Estimation for Sketched SVD via the Bootstrap ICML 2020 Interpretable Multimodal Learning for Intelligent Regulation in Online Payment Systems IJCAI 2020 Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer CVPR 2020 Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension ICML 2020 Approximate Kernel Selection with Strong Approximate Consistency AAAI 2019 Average Case Column Subset Selection for Entrywise ℓ_1-Norm Loss NeurIPS 2019 High-Dimensional Optimization in Adaptive Random Subspaces NeurIPS 2019 Incremental Randomized Sketching for Online Kernel Learning ICML 2019 Massively scalable Sinkhorn distances via the Nyström method NeurIPS 2019 Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation NeurIPS 2019 Towards a Zero-One Law for Column Subset Selection NeurIPS 2019 Differentially Private Robust Low-Rank Approximation NeurIPS 2018 Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices ICML 2018 On Fast Leverage Score Sampling and Optimal Learning NeurIPS 2018 Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data JMLR 2018