About

I am a Ph.D. candidate in the Department of Computer Science at Purdue, advised by Prof. Jean Honorio. Previously I obtained my B.S. degree in Computer Science from University of Rochester, where I was advised by Dr. Ji Liu.

My research focuses on developing statistically and computationally efficient algorithms with provable guarantees in the field of structured prediction, community detection, and related applications.

Publications

1. Provable Guarantees for Sparsity Recovery with Deterministic Missing Data Patterns
   Chuyang Ke, Jean Honorio
   (Under submission)
2. Exact Inference with Latent Variables in an Arbitrary Domain
   Chuyang Ke, Jean Honorio
   (Under submission)
3. Dual Convexified Convolutional Neural Networks
   Site Bai, Chuyang Ke, Jean Honorio
   (Under submission)
4. Exact Partitioning of High-order Models with a Novel Convex Tensor Cone Relaxation
   Chuyang Ke, Jean Honorio
   JMLR, 2022
5. Federated Myopic Community Detection with One-shot Communication
   Chuyang Ke, Jean Honorio
   AISTATS, 2022
6. A Thorough View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy
   Kevin Bello, Chuyang Ke, Jean Honorio
   AISTATS, 2022
7. Exact Partitioning of High-order Planted Models with a Tensor Nuclear Norm Constraint
   Chuyang Ke, Jean Honorio
   ICASSP, 2022
8. Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection
   Jiajun Liang, Chuyang Ke, Jean Honorio
   ISIT, 2021
9. Information-theoretic Limits for Community Detection in Network Models
   Chuyang Ke, Jean Honorio
   NeurIPS, 2018
10. University of Rochester WMT 2017 NMT System Submission
    Chester Holtz, Chuyang Ke, Daniel Gildea
    WMT, 2017
11. On The Projection Operator to A Three-view Cardinality Constrained Set
    Haichuan Yang, Shupeng Gui, Chuyang Ke, Daniel Stefankovic, Ryohei Fujimaki, Ji Liu
    ICML, 2017
12. Prognostics of Surgical Site Infections Using Dynamic Health Data
    Chuyang Ke, Yan Jin, Heather Evans, Bill Lober, Xiaoning Qian, Ji Liu, Shuai Huang
    Journal of Biomedical Informatics, 2017

Teaching

• Head TA, CS 182 Foundations of Computer Science, Purdue, Fall 2021
• TA, CS 373 Data Mining and Machine Learning, Purdue, Spring 2021
• TA, CS 578 Statistical Machine Learning, Purdue, Fall 2020
• TA, CS 182 Foundations of Computer Science, Purdue, Spring 2018
• TA, CS 182 Foundations of Computer Science, Purdue, Fall 2017
• TA, CSC 240 Data Mining, Univ. of Rochester, Spring 2017
• TA, MTH 150 Discrete Mathematics, Univ. of Rochester, Fall 2015
• TA, MTH 150 Discrete Mathematics, Univ. of Rochester, Spring 2015
• TA, MTH 150 Discrete Mathematics, Univ. of Rochester, Fall 2014

Academic Service

• Reviewer, AISTATS, 2022, 2023
• Reviewer, ICLR, 2021, 2022, 2023
• Reviewer, ICML, 2021, 2022
• Reviewer, NeurIPS, 2019, 2020, 2021, 2022
• Reviewer, IJCAI, 2020
• Reviewer, IEEE Transactions on Information Theory