Zhenxun Zhuang

According to our database, Zhenxun Zhuang authored at least 11 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Adaptive Strategies in Non-convex Optimization.

Zhenxun Zhuang

CoRR, 2023

2022

Adaptive strategies in non-convex optimization

Zhenxun Zhuang

PhD thesis, 2022

Understanding AdamW through Proximal Methods and Scale-Freeness.

Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky, Francesco Orabona

Trans. Mach. Learn. Res., 2022

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks.

Mingrui Liu, Zhenxun Zhuang, Yunwei Lei, Chunyang Liao

CoRR, 2022

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks.

Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robustness to Unbounded Smoothness of Generalized SignSGD.

Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance.

Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Exponential Step Sizes for Non-Convex Optimization.

Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona

CoRR, 2020

No-Regret Non-Convex Online Meta-Learning.

Zhenxun Zhuang, Yunlong Wang, Kezi Yu, Songtao Lu

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Online Meta-Learning on Non-convex Setting.

Zhenxun Zhuang, Yunlong Wang, Kezi Yu, Songtao Lu

CoRR, 2019

Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization.

Zhenxun Zhuang, Ashok Cutkosky, Francesco Orabona

Proceedings of the 36th International Conference on Machine Learning, 2019