{"total":15,"rows":[{"id":"2406.11151","title":"Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning","created":"2024-06-17","cited_by_count":11,"area":null},{"id":"2206.02702","title":"Stochastic Variance-Reduced Newton: Accelerating Finite-Sum Minimization with Large Batches","created":"2022-06-06","cited_by_count":9,"area":null},{"id":"2304.12465","title":"Robust, randomized preconditioning for kernel ridge regression","created":"2023-04-24","cited_by_count":9,"area":null},{"id":"2405.05818","title":"Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems","created":"2024-05-09","cited_by_count":7,"area":null},{"id":"2106.12231","title":"ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions","created":"2021-06-23","cited_by_count":6,"area":null},{"id":"2405.05865","title":"Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning","created":"2024-05-09","cited_by_count":4,"area":null},{"id":"2410.10258","title":"Revisiting Matrix Sketching in Linear Bandits: Achieving Sublinear Regret via Dyadic Block Sketching","created":"2024-10-14","cited_by_count":4,"area":null},{"id":"2602.06880","title":"Decoupling Variance and Scale-Invariant Updates in Adaptive Gradient Descent for Unified Vector and Matrix Optimization","created":"2026-02-06","cited_by_count":4,"area":null},{"id":"2403.08585","title":"Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems","created":"2024-03-13","cited_by_count":3,"area":null},{"id":"2404.14758","title":"Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients","created":"2024-04-23","cited_by_count":3,"area":null},{"id":"2106.12060","title":"Faster Randomized Methods for Orthogonality Constrained Problems","created":"2021-06-22","cited_by_count":2,"area":null},{"id":"2507.11724","title":"Approaching Optimality for Solving Dense Linear Systems with Low-Rank Structure","created":"2025-07-15","cited_by_count":2,"area":null},{"id":"2305.17283","title":"Sharpened Lazy Incremental Quasi-Newton Method","created":"2023-05-26","cited_by_count":1,"area":null},{"id":"2305.17435","title":"On the Noise Sensitivity of the Randomized SVD","created":"2023-05-27","cited_by_count":0,"area":null},{"id":"2609.38565","title":"The Advantages of Fresh Sketching for Ridge Regression","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}