Research

I am currently pursuing research in learning theory, in particular, active learning and reinforcement learning.

Preprints

  1. Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity
    with Simon Du, Jason Lee and Ruosong Wang
    Manuscript

Publications

  1. Point Location and Active Learning: Learning Halfspaces Almost Optimally
    with Max Hopkins, Daniel Kane And Shachar Lovett
    Accepted to the 61st Annual Symposium on Foundations of Computer Science (FOCS 2020).

  2. Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes
    with Alekh Agarwal, Sham Kakade and Jason Lee
    Accepted to the 33rd annual Conference on Learning Theory (COLT 2020).

  3. Noise-tolerant, Reliable Active Classification with Comparison Queries
    with Max Hopkins, Daniel Kane And Shachar Lovett
    Accepted to the 33rd annual Conference on Learning Theory (COLT 2020).