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cs.DS2026
Algorithms with Polynomially-Improved Approximation Factors for the Norm, and Applications
Samuel B. Hopkins, Stefan Tiegel
The norm of a matrix is defined as . We give…
cs.DS2024
SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More
Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia +1
We study for random rectangular matrices. If is an matrix with independent Gaussian entries, we give a new family of…
cs.DS2024
SoS Certifiability of Subgaussian Distributions and its Algorithmic Applications
Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia +1
We prove that there is a universal constant so that for every , every centered subgaussian distribution on , and every even $p \in…