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Ankish Chandresh

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#machine learning May 2026

Riemannian Optimization for Hadamard Products of Low-Rank Matrices

This work proposes a novel block-diagonal Riemannian metric derived from the pullback of the Frobenius inner product and develops a Riemannian gradient descent algorithm that uses a tuning-free Gaussian step size and scales linearly in the number of observed entries per iteration.

Pratik Jawanpuria, Ankish Chandresh, Bamdev Mishra · arXiv.org · 0 citations