Frank Wu

I'm a Master's student in Machine Learning at Carnegie Mellon University. I'm interested in exploring emerging paradigms for training neural networks, with an emphasis on reinforcement learning, continual learning, and generalization.

Previously, I was a Machine Learning Engineer at Alibaba Group, where I built action recognition models and visual search engines serving 50M+ daily active users. I received my B.A. in Computer Science & Mathematics from New York University.

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News

  • Oct 2025: Our paper on local reinforcement learning accepted to ICLR 2026!
  • Aug 2025: Started my Master's program in Machine Learning at Carnegie Mellon University.
  • Jun 2024: Graduated from New York University with B.A. in Computer Science & Mathematics.

Publications

Local Reinforcement Learning with Action-Conditioned Root Mean Squared Q-Functions
Frank Wu, Mengye Ren
International Conference on Learning Representations (ICLR), 2026
website / arXiv / code

We propose ARQ, which unifies Forward-Forward learning with TD updates for fully local reinforcement learning using action-conditioned, vector-valued value functions; we achieve 50% average return improvement and match backprop-based baselines on MinAtar and DeepMind Control Suite.


Website design inspired by Jon Barron