low-rank matrix

Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix ICML 2020 Pursuit of Low-Rank Models of Time-Varying Matrices Robust to Sparse and Measurement Noise AAAI 2020 Recommendation on a Budget: Column Space Recovery from Partially Observed Entries with Random or Active Sampling AISTATS 2020 Robust Low-Rank Discovery of Data-Driven Partial Differential Equations AAAI 2020 Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation NeurIPS 2020 Accelerated Alternating Projections for Robust Principal Component Analysis JMLR 2019 Bilinear Bandits with Low-rank Structure ICML 2019 Decentralized sketching of low rank matrices NeurIPS 2019 Efficient Full-Matrix Adaptive Regularization ICML 2019 Exponentially convergent stochastic k-PCA without variance reduction NeurIPS 2019 Fast Algorithms for Sparse Reduced-Rank Regression AISTATS 2019 Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems AISTATS 2019 High-dimensional Varying Index Coefficient Models via Stein's Identity JMLR 2019 Low-Rank Tensor Completion With a New Tensor Nuclear Norm Induced by Invertible Linear Transforms CVPR 2019 Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption NeurIPS 2019 Nonconvex Matrix Factorization from Rank-One Measurements AISTATS 2019 Personalizing Many Decisions with High-Dimensional Covariates NeurIPS 2019 RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices CVPR 2019 Robust Matrix Completion from Quantized Observations AISTATS 2019 Robust Principal Component Analysis-Based Infrared Small Target Detection AAAI 2019 Spectrum Estimation from a Few Entries JMLR 2019 Universality in Learning from Linear Measurements NeurIPS 2019 A Dual Framework for Low-rank Tensor Completion NeurIPS 2018 An ℓ_∞ Eigenvector Perturbation Bound and Its Application JMLR 2018 A Unified Framework for Structured Low-rank Matrix Learning ICML 2018