low-rank approximation

GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking NeurIPS 2018 Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski p-Norms ICML 2018 Low-rank passthrough neural networks ACL 2018 Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering ICML 2018 Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch NeurIPS 2018 Multi-Scale Weighted Nuclear Norm Image Restoration CVPR 2018 Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration CVPR 2018 Power-law Distribution Aware Trust Prediction IJCAI 2018 Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data JMLR 2018 Ridge Regression and Provable Deterministic Ridge Leverage Score Sampling NeurIPS 2018 Scalable Robust Matrix Factorization with Nonconvex Loss NeurIPS 2018 Self-Supervised Deep Low-Rank Assignment Model for Prototype Selection IJCAI 2018 Sublinear Time Low-Rank Approximation of Distance Matrices NeurIPS 2018 Subspace Embedding and Linear Regression with Orlicz Norm ICML 2018 The Price of Fair PCA: One Extra dimension NeurIPS 2018 Towards Binary-Valued Gates for Robust LSTM Training ICML 2018 Adaptive Randomized Dimension Reduction on Massive Data JMLR 2017 Algorithms for ℓ_p Low-Rank Approximation ICML 2017 An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation ICML 2017 Approximation Algorithms for ℓ_0-Low Rank Approximation NeurIPS 2017 Category-aware Next Point-of-Interest Recommendation via Listwise Bayesian Personalized Ranking IJCAI 2017 Certifiably Optimal Low Rank Factor Analysis JMLR 2017 Compact Matrix Factorization With Dependent Subspaces CVPR 2017 Co-Occurring Directions Sketching for Approximate Matrix Multiply AISTATS 2017 Fast Recursive Low-rank Tensor Learning for Regression IJCAI 2017