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Biography

I am currently an assistant professor at the Department of Computer Science, Shanghai University of Finance and Economics. I obtained my Ph.D. in Computer Science from Shanghai Jiao Tong University in 2020 and received my B.S. in Computer Science from the ACM Class at Shanghai Jiao Tong University in 2014.

I am broadly interested in fundamental techniques and theories of machine learning, including optimization, generalization, representation learning, learning theory, principled design of neural networks, generative models, etc.

Ultimately, I aim to lay a solid foundation for artificial intelligence.

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Selected Works

Learning Personalizable Clustered Embedding for Recommender Systems. [acm][pdf]

• Yizhou Chen, Guangda Huzhang, Anxiang Zeng, Qingtao Yu, Hui Sun, Heng-yi Li, Jingyi Li, Yabo Ni, Han Yu, Zhiming Zhou.
• ACM Transactions on Recommender Systems (TORS), 2025, Volume 3, Issue 3.

Residual Multi-Task Learner for Applied Ranking. [openreview][acm][slide]

• Cong Fu, Kun Wang, Jiahua Wu, Yizhou Chen, Guangda Huzhang, Yabo Ni, Anxiang Zeng, Zhiming Zhou.
• ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.

Recurrent Temporal Revision Graph Networks. [openreview][acm] [arxiv]

• Yizhou Chen, Anxiang Zeng, Guangda Huzhang, Qingtao Yu, Kerui Zhang, Cao Yuanpeng, Kangle Wu, Han Yu, Zhiming Zhou.
• Annual Conference on Neural Information Processing Systems (NeurIPS), 2023.

Clustered Embedding Learning for Recommender Systems. [acm] [arxiv]

• Yizhou Chen, Guangda Huzhang, Anxiang Zeng, Qingtao Yu, Hui Sun, Heng-yi Li, Jingyi Li, Yabo Ni, Han Yu, Zhiming Zhou.
• ACM Web Conference (WWW), 2023.

Lipschitz Generative Adversarial Nets. [pmlr] [arxiv] [slide] [code] [code] [code]

• Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang.
• International Conference on Machine Learning (ICML), 2019.

AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods. [openreview] [arxiv] [poster] [code]

• Zhiming Zhou*, Qingru Zhang*, Guansong Lu, Hongwei Wang, Weinan Zhang, Yong Yu.
• International Conference on Learning Representations (ICLR), 2019.

Activation Maximization Generative Adversarial Nets. [openreview] [arxiv] [code] [code]

• Zhiming Zhou, Han Cai, Shu Rong, Yuxuan Song, Kan Ren, Weinan Zhang, Jun Wang, Yong Yu.
• International Conference on Learning Representations (ICLR), 2018.

Sparse-as-Possible SVBRDF Acquisition. [acm] [pdf] [slide]

• Zhiming Zhou, Guojun Chen, Yue Dong, David Wipf, Yong Yu, John Snyder, Xin Tong.
• ACM Transactions on Graphics (TOG) - ACM SIGGRAPH Asia, 2016.