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Exact expressions for double descent and implicit regularization via surrogate random design.

, , and . NeurIPS, (2020)

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Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds., , and . CoRR, (2017)Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning., and . CoRR, (2018)JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks., , and . CoRR, (2019)Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms., and . KDD, page 359-368. ACM, (2015)CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT)., , , , , and . CoRR, (2023)Newton-MR: Newton's Method Without Smoothness or Convexity., , , and . CoRR, (2018)Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix, , and . SIAM J. Comput., 36 (1): 158-183 (2006)CUR matrix decompositions for improved data analysis, and . Proceedings of the National Academy of Sciences, 106 (3): 697-702 (2009)Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels., , , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 485-493. JMLR.org, (2014)Revisiting the Nystrom method for improved large-scale machine learning., and . ICML (3), volume 28 of JMLR Workshop and Conference Proceedings, page 567-575. JMLR.org, (2013)