PhD and RA positions, 香港中文大学（深圳）

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There are positions for two Ph.D. students and several RAs in the field of machine learning and optimization at The Chinese University of Hong Kong, Shenzhen.  If you are interested, you can contact lixiao@cuhk.edu.cn with your CV, transcripts, and any other supporting materials.

Here are some concrete research directions (but not limited to):

1. Nonconvex and/or nonsmooth optimization. This topic includes: 1) Designing efficient and provable first-order optimization algorithms for problems arising in machine learning and data science. 2) Designing efficient nonsmooth optimization algorithms for nonsmooth problems as these types of problems are popular for robust estimation in machine learning and data science. 3) Analyzing specific (not that scary) nonconvex problems, including its global optimization geometry, local geometry, and regularities, etc.

2. (deep) Reinforcement learning. This direction is about to design and analyze sample-efficient algorithms for model-based and/or model-free RL. In addition, we also seek for theoretical interpretations for shallow nets, such as generalization performance and algorithmic convergence.

3. Applications. This direction includes certain applications of optimization theory and machine learning to signal processing and computational imaging.


Please click the following link to see more details:

sites.google.com/view/xli-phd-recruit/home

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给老师发了邮件，可惜没有收到回复，不知道老师的要求是什么