Publications

Preprints
  1. Training By Vanilla SGD with Larger Learning Rates
    Yueyao Yu, Jie Wang, Wenye Li, Yin Zhang.

  2. Achievable Rate and Latency of Line Networks with Outage Links
    Yanyan Dong, Shenghao Yang, Jie Wang, Fan Cheng. Submitted to IEEE Journal on Selected Areas in Information Theory

  3. Variable Selection for Kernel Two-Sample Tests
    Jie Wang, Santanu Dey, Yao Xie. (Selected for Poster Presentation at Mixed Integer Programming (MIP) Workshop 2023, to be submitted to Operations Research)

  4. Regularization for Adversarial Robust Learning [Slides]
    Jie Wang, Rui Gao, Yao Xie. (Winner of the 18th INFORMS DMDA Workshop Best Paper Competition Award, 2 out of 57, to be submitted to Operations Research)

  5. Sparse Degree Optimization for BATS Codes
    Hoover H. F. Yin, Jie Wang.

  6. Bias, Variance, and Costs Tradeoff in Multi-level Monte-Carlo for Stochastic Optimization with Biased Oracles
    Yifan Hu, Jie Wang, Xin Chen, Niao He. Journal version to be submitted to Operations Research

Conference Proceedings
  1. Achievable Rate and Latency of Line Networks with Outage Links
    Yanyan Dong, Shenghao Yang, Jie Wang, Fan Cheng. 2024 IEEE International Symposium on Information Theory

  2. Distributionally Robust Degree Optimization for BATS Codes
    Hoover H. F. Yin, Jie Wang, Sherman S. M. Chow. 2024 IEEE International Symposium on Information Theory

  3. Non-Convex Robust Hypothesis Testing using Sinkhorn Uncertainty Sets
    Jie Wang, Rui Gao, Yao Xie. 2024 IEEE International Symposium on Information Theory

  4. Conditional Stochastic Bilevel Optimization
    Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Kuhn. NeurIPS 2023 (Journal version to be submitted to Operations Research)

  5. Reliable Adaptive Recoding for Batched Network Coding with Burst-Noise Channels
    Jie Wang, Talha Bozkus, Yao Xie, Urbashi Mitra. Asilomar 2023

  6. Improving Sepsis Prediction Model Generalization With Optimal Transport
    Jie Wang, Ronald Moore, Rishikesan Kamaleswaran, Yao Xie. 2022 Machine Learning for Health (ML4H)

  7. A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets
    Jie Wang, Yao Xie. 2022 IEEE International Symposium on Information Theory (ISIT)

  8. Two-sample Test with Kernel Projected Wasserstein Distance
    Jie Wang, Rui Gao, Yao Xie. 2022 Artificial Intelligence and Statistics (AISTATS) (Oral Presentation! Rate: 44/1685=0.026)

  9. Two-sample Test using Projected Wasserstein Distance
    Jie Wang, Rui Gao, Yao Xie. 2021 IEEE International Symposium on Information Theory (ISIT)

  10. Small-Sample Inferred Adaptive Recoding for Batched Network Coding
    Jie Wang, Zhiyuan Jia, Hoover H. F. Yin, Shenghao Yang. 2021 IEEE International Symposium on Information Theory (ISIT)

  11. Upper Bound Scalability on Achievable Rates of Batched Codes for Line Networks
    Shenghao Yang, Jie Wang. 2020 IEEE International Symposium on Information Theory (ISIT)

  12. On the Capacity Scalability of Line Networks with Buffer Size Constraints
    Shenghao Yang, Jie Wang, Yanyan Dong, Yiheng Zhang. 2019 IEEE International Symposium on Information Theory (ISIT)

  13. On the Tightness of a Cut-Set Bound on Network Function Computation
    Jie Wang, Shenghao Yang, Congduan Li. 2018 IEEE International Symposium on Information Theory (ISIT)

  14. Efficient Underwater Sensor Network Data Collection Employing Unmanned Ships
    Jie Wang, Jun Ma, Jianyu Yang, Shenghao Yang. The 14th International Conference on Underwater Networks & Systems (WUWNet’19), At Atlanta, GA, USA (Extended Manuscript)

Chapter
  1. Finite-length Code and Application in Network Coding
    Shenghao Yang, Yanyan Dong, Jie Wang. IEEE INFORMATION THEORY SOCIETY GUANGZHOU CHAPTER NEWSLETTER, No.1, July 2020.