32 citations · 80 across the 15 of their papers we have counts for
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cs.LG2022
Formal guarantees for heuristic optimization algorithms used in machine learning
Xiaoyu Li
Recently, Stochastic Gradient Descent (SGD) and its variants have become the dominant methods in the large-scale optimization of machine learning (ML) problems. A variety of strate…
cs.LG2021
Toward Communication Efficient Adaptive Gradient Method
Xiangyi Chen, Xiaoyun Li, Ping Li
In recent years, distributed optimization is proven to be an effective approach to accelerate training of large scale machine learning models such as deep neural networks. With the…
cs.LG2021★ 1 cited
On the Last Iterate Convergence of Momentum Methods
Xiaoyu Li, Mingrui Liu, Francesco Orabona
SGD with Momentum (SGDM) is a widely used family of algorithms for large-scale optimization of machine learning problems. Yet, when optimizing generic convex functions, no advantag…