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Zhenxun Zhuang
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Books and Theses
- 2022
- [b1]Zhenxun Zhuang:
Adaptive strategies in non-convex optimization. Boston University, USA, 2022
Journal Articles
- 2022
- [j1]Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky
, Francesco Orabona:
Understanding AdamW through Proximal Methods and Scale-Freeness. Trans. Mach. Learn. Res. 2022 (2022)
Conference and Workshop Papers
- 2022
- [c5]Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang:
Robustness to Unbounded Smoothness of Generalized SignSGD. NeurIPS 2022 - [c4]Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao:
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. NeurIPS 2022 - 2021
- [c3]Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona:
A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance. ICML 2021: 6553-6564 - 2020
- [c2]Zhenxun Zhuang, Yunlong Wang, Kezi Yu, Songtao Lu:
No-Regret Non-Convex Online Meta-Learning. ICASSP 2020: 3942-3946 - 2019
- [c1]Zhenxun Zhuang, Ashok Cutkosky
, Francesco Orabona:
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization. ICML 2019: 7664-7672
Informal and Other Publications
- 2023
- [i7]Zhenxun Zhuang:
Adaptive Strategies in Non-convex Optimization. CoRR abs/2306.10278 (2023) - 2022
- [i6]Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky, Francesco Orabona:
Understanding AdamW through Proximal Methods and Scale-Freeness. CoRR abs/2202.00089 (2022) - [i5]Mingrui Liu, Zhenxun Zhuang, Yunwei Lei, Chunyang Liao:
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. CoRR abs/2205.05040 (2022) - [i4]Michael Crawshaw, Mingrui Liu, Francesco Orabona
, Wei Zhang, Zhenxun Zhuang:
Robustness to Unbounded Smoothness of Generalized SignSGD. CoRR abs/2208.11195 (2022) - 2020
- [i3]Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona:
Exponential Step Sizes for Non-Convex Optimization. CoRR abs/2002.05273 (2020) - 2019
- [i2]Zhenxun Zhuang, Ashok Cutkosky, Francesco Orabona:
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization. CoRR abs/1901.09068 (2019) - [i1]Zhenxun Zhuang, Yunlong Wang, Kezi Yu, Songtao Lu:
Online Meta-Learning on Non-convex Setting. CoRR abs/1910.10196 (2019)
Coauthor Index
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