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math.OC2021★ 6 cited
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization
Tian Ye, Simon S. Du
We study the asymmetric low-rank factorization problem: \[\min_{\mathbf{U} \in \mathbb{R}^{m \times d}, \mathbf{V} \in \mathbb{R}^{n \times d}} \frac{1}{2}\|\mathbf{U}\mathbf{V}^\t…
math.OC2020★ 1 cited
DEED: A General Quantization Scheme for Communication Efficiency in Bits
Tian Ye, Peijun Xiao, Ruoyu Sun
In distributed optimization, a popular technique to reduce communication is quantization. In this paper, we provide a general analysis framework for inexact gradient descent that i…