I’m a fifth-year PhD student in the Department of Computer Science at Princeton University. I’m fortunate to be advised by Professor Elad Hazan. Before Princeton, I received a B.S. degree in Math from Peking University, advised by Professor Liwei Wang. I’m interested in learning theory.

Publications

• When is Inductive Inference Possible?.
  Zhou Lu. Neurips 2024 (spotlight).
• Online Control in Population Dynamics.
  Noah Golowich, Elad Hazan, Zhou Lu, Dhruv Rohatgi, Y. Jennifer Sun. Neurips 2024.
• Tight Rates for Bandit Control Beyond Quadratics.
  Y. Jennifer Sun, Zhou Lu. Neurips 2024.
• Adaptive Online Learning of Quantum States.
  Xinyi Chen, Elad Hazan, Tongyang Li, Zhou Lu, Xinzhao Wang, Rui Yang. Quantum.
• Adaptive Regret for Bandits Made Possible: Two Queries Suffice.
  Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David Woodruff, Elad Hazan. ICLR 2024.
• On the Computational Benefit of Multimodal Learning.
  Zhou Lu. ALT 2024.
• A Theory of Multimodal Learning.
  Zhou Lu. Neurips 2023.
• Projection-free adaptive regret with membership oracles.
  Zhou Lu, Nataly Brukhim, Paula Gradu, Elad Hazan. ALT 2023.
• Non-convex online learning via algorithmic equivalence.
  Udaya Ghai, Zhou Lu, Elad Hazan. Neurips 2022.
• Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons.
  Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang. ICML 2021.
• Boosting for control of dynamical systems.
  Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu. ICML 2020.
• The expressive power of neural networks: A view from the width.
  Zhou Lu, Hongming Pu, Feicheng Wang, Zhiqiang Hu, Liwei Wang. NIPS 2017.

Services

Reviewers for Neurips, ICML, ICLR, COLT, STOC, Mathematical Programming, IEEE-TPAMI.