My research interests focus on randomized algorithms, and their applications to distributed computing and large-scale machine learning.

My research is supported by the following grants: NSF CCF-1525024 and NSF IIS-1633215


  1. Submodular Maximization over Sliding Windows, [arXiv]
    with Huy L. Nguyen and Qin Zhang


  1. AISTATS’19, Stochastic Negative Mining for Learning with Large Output Spaces,
    Sashank J. Reddi, Satyen Kale, Felix X. Yu, Dan Holtmann-Rice, Jiecao Chen, Sanjiv Kumar

  2. NIPS’18, Tight Bounds for Collaborative PAC Learning via Multiplicative Weights, [arXiv]
    with Qin Zhang and Yuan Zhou

  3. NIPS’18, A Practical Algorithm for Distributed Clustering and Outlier Detection [arXiv]
    with Erfan Sadeqi Azer and Qin Zhang

  4. PODS’18, Distinct Sampling on Streaming Data with Near-Duplicates,
    with Qin Zhang

  5. ICML’17, Adapting Kernel Representations Online using Submodular Maximization,
    Yangchen Pan, Matthew Schlegel, Jiecao Chen, Martha White

  6. ICML’17, Adaptive Multiple-Arm Identification, [conference version], [full version]
    with Xi Chen, Qin Zhang, and Yuan Zhou

  7. VLDB’17, Bias-Aware Sketches, [arXiv]
    with Qin Zhang

  8. NIPS’16, Communication-Optimal Distributed Clustering, [conference version], [full version]
    with He Sun, David Woodruff, and Qin Zhang

  9. ITCS’16, On Sketching Quadratic Forms
    with Alexandr Andoni, Robert Krauthgamer, Bo Qin, David Woodruff, and Qin Zhang

  10. Algorithmica 2016, Improved Algorithms for Distributed Entropy Monitoring
    with Qin Zhang



  • Reviewer/Sub-Reviewer for: CIKM’14, ISAAC’14, NIPS’16’17, PODS’17, COLT’17, VLDB Journal, AAAI’18, ICLR’18, ICML’18, NIPS’18, ICML’19


Here is a reading group I organized at SOIC.