matrix computation

Approximating the Top Eigenvector in Random Order Streams NeurIPS 2024 Asynchronous Randomized Trace Estimation AISTATS 2024 Optimized Speculative Sampling for GPU Hardware Accelerators EMNLP 2024 CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra NeurIPS 2023 Fast Attention Requires Bounded Entries NeurIPS 2023 Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations NeurIPS 2023 Fast Finite Width Neural Tangent Kernel ICML 2022 Improved analysis of randomized SVD for top-eigenvector approximation AISTATS 2022 A Comprehensively Tight Analysis of Gradient Descent for PCA NeurIPS 2021 A Practical Riemannian Algorithm for Computing Dominant Generalized Eigenspace UAI 2020 Scikit-network: Graph Analysis in Python JMLR 2020 Approximating the Permanent by Sampling from Adaptive Partitions NeurIPS 2019 Efficient coordinate-wise leading eigenvector computation ALT 2018 Exploiting Numerical Sparsity for Efficient Learning : Faster Eigenvector Computation and Regression NeurIPS 2018 Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis ICML 2017 Coordinate-wise Power Method NeurIPS 2016 Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis ICML 2016 Faster Eigenvector Computation via Shift-and-Invert Preconditioning ICML 2016 Large-scale log-determinant computation through stochastic Chebyshev expansions ICML 2015 large scale canonical correlation analysis with iterative least squares NeurIPS 2014