matrix sketching

FLRQ: Faster LLM Quantization with Flexible Low-Rank Matrix Sketching AAAI 2026 Query Efficient Structured Matrix Learning COLT 2026 Fast Second-Order Online Kernel Learning Through Incremental Matrix Sketching and Decomposition IJCAI 2025 Matrix Product Sketching via Coordinated Sampling ICLR 2025 Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation ICML 2025 Distributed Least Squares in Small Space via Sketching and Bias Reduction NeurIPS 2024 Efficient Leverage Score Sampling for Tensor Train Decomposition NeurIPS 2024 Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching ICML 2024 Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching CVPR 2024 Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels AISTATS 2024 A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging NeurIPS 2023 A Nearly-Optimal Bound for Fast Regression with ℓ_∞ Guarantee ICML 2023 Projection-free Online Exp-concave Optimization COLT 2023 Sharper Bounds for ℓ_p Sensitivity Sampling ICML 2023 Towards Optimal Effective Resistance Estimation NeurIPS 2023 Iterative Double Sketching for Faster Least-Squares Optimization ICML 2022 Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences NAACL 2022 Approximate Multiplication of Sparse Matrices with Limited Space AAAI 2021 Communication-Efficient Distributed Covariance Sketch, with Application to Distributed PCA JMLR 2021 Fast and accurate randomized algorithms for low-rank tensor decompositions NeurIPS 2021 Matrix Sketching for Secure Collaborative Machine Learning ICML 2021 MetaGrad: Adaptation using Multiple Learning Rates in Online Learning JMLR 2021 Non-PSD matrix sketching with applications to regression and optimization UAI 2021 Optimal Sketching for Trace Estimation NeurIPS 2021 Reduced-Rank Regression with Operator Norm Error COLT 2021