numerical linear algebra

Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems JMLR 2025 When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time? AISTATS 2025 Approximating the Top Eigenvector in Random Order Streams NeurIPS 2024 Faster Randomized Methods for Orthogonality Constrained Problems JMLR 2024 CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra NeurIPS 2023 The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium ICLR 2023 Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms JMLR 2022 Learning Green's functions associated with time-dependent partial differential equations JMLR 2022 Subquadratic Kronecker Regression with Applications to Tensor Decomposition NeurIPS 2022 Analysis of stochastic Lanczos quadrature for spectrum approximation ICML 2021 A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples ICML 2021 Dynamic Trace Estimation NeurIPS 2021 Fast and accurate randomized algorithms for low-rank tensor decompositions NeurIPS 2021 Fast Sketching of Polynomial Kernels of Polynomial Degree ICML 2021 Oblivious Sketching for Logistic Regression ICML 2021 On the Riemannian Search for Eigenvector Computation JMLR 2021 Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices AAAI 2021 Single Pass Entrywise-Transformed Low Rank Approximation ICML 2021 Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms AISTATS 2020 Entrywise convergence of iterative methods for eigenproblems NeurIPS 2020 Error Estimation for Sketched SVD via the Bootstrap ICML 2020 Kernel Methods Through the Roof: Handling Billions of Points Efficiently NeurIPS 2020 Minimax Rank-$1$ Matrix Factorization AISTATS 2020 Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling ICML 2020 Efficient Symmetric Norm Regression via Linear Sketching NeurIPS 2019