Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization. - Zhenxun Zhuang; Ashok Cutkosky; Francesco Orabona (ICML, 2019)

Online Meta-Learning on Non-convex Setting. - Zhenxun Zhuang; Yunlong Wang 010; Kezi Yu; Songtao Lu (CoRR, 2019)

No-Regret Non-Convex Online Meta-Learning. - Zhenxun Zhuang; Yunlong Wang 010; Kezi Yu; Songtao Lu (ICASSP, 2020)

Exponential Step Sizes for Non-Convex Optimization. - Xiaoyu Li; Zhenxun Zhuang; Francesco Orabona (CoRR, 2020)

A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance. - Xiaoyu Li; Zhenxun Zhuang; Francesco Orabona (ICML, 2021)

Robustness to Unbounded Smoothness of Generalized SignSGD. - Michael Crawshaw; Mingrui Liu; Francesco Orabona; Wei Zhang 022; Zhenxun Zhuang (NeurIPS, 2022)

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. - Mingrui Liu; Zhenxun Zhuang; Yunwen Lei; Chunyang Liao (NeurIPS, 2022)

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. - Mingrui Liu; Zhenxun Zhuang; Yunwei Lei; Chunyang Liao (CoRR, 2022)

Understanding AdamW through Proximal Methods and Scale-Freeness. - Zhenxun Zhuang; Mingrui Liu; Ashok Cutkosky; Francesco Orabona (Trans. Mach. Learn. Res., 2022)

Adaptive strategies in non-convex optimization - Zhenxun Zhuang (2022)

Adaptive Strategies in Non-convex Optimization. - Zhenxun Zhuang (CoRR, 2023)