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Zhaoran Wang

  • 328 Citations
20122022

Research output per year

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Personal profile

Research Interests

Professor Zhaoran’s research is at the interface of statistics and optimization in machine learning. He has specific interests in understanding the tradeoff between statistical accuracy and computational effort as well as establishing provable guarantees for non-convex problems in statistical learning.

Education/Academic qualification

Operations Research and Financial Engineering, PhD, Princeton University

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Grants

HDR TRIPODS: Collaborative Research: Institute for Data, Econometrics, Algorithms and Learning .

Hartline, J. D., Auerbach, E. J., Berry, R. A., Canay, I. A., Guo, D., Horowitz, J. L., Makarychev, K., Vijayaraghavan, A. & Wang, Z.

National Science Foundation

9/15/19 → 8/31/22

Project: Research project

    • Research Output

    Accelerating nonconvex learning via replica exchange Langevin diffusion

    Chen, Y., Chen, J., Dong, J., Peng, J. & Wang, Z., Jan 1 2019.

    Research output: Contribution to conference › Paper

    • High-dimensional Varying Index Coefficient Models via Stein’s Identity

    Na, S., Yang, Z., Wang, Z. & Kolar, M., Oct 1 2019, In : Journal of Machine Learning Research. 20

    Research output: Contribution to journal › Article

    • Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic Decomposition

    Huang, K., Yang, Z., Wang, Z. & Hong, M., Jun 2019, 2019 IEEE Data Science Workshop, DSW 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 295-299 5 p. 8755551. (2019 IEEE Data Science Workshop, DSW 2019 - Proceedings).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    • Misspecified nonconvex statistical optimization for sparse phase retrieval

    Yang, Z., Yang, L. F., Fang, E. X., Zhao, T., Wang, Z. & Neykov, M., Jul 1 2019, In : Mathematical Programming. 176, 1-2, p. 545-571 27 p.

    Research output: Contribution to journal › Article

    • 3 Scopus citations

    Off-policy evaluation and learning from logged bandit feedback: Error reduction via surrogate policy

    Xie, Y., Liu, Q., Zhou, Y., Liu, B., Wang, Z. & Peng, J., Jan 1 2019.

    Research output: Contribution to conference › Paper