Fast and Low-Memory Compressive Sensing Algorithms for Low Tucker-Rank Tensor Approximation...

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Stochastic gradient descent for streaming linear and rectified linear systems with Massart noise

H Jeong, D Needell, E Rebrova - arxiv preprint arxiv:2403.01204, 2024 - arxiv.org
We propose SGD-exp, a stochastic gradient descent approach for linear and ReLU
regressions under Massart noise (adversarial semi-random corruption model) for the fully …
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Efficient Randomized Algorithms for Fixed Precision Problem of Approximate Tucker Decomposition

M Che, Y Wei, H Yan - SIAM Journal on Matrix Analysis and Applications, 2025 - SIAM
In this paper, we focus on the fixed-precision problem for the approximate Tucker
decomposition of any tensor. First, we modify several structured matrices for the adaptive …
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