About

I am a 6th year Ph.D. candidate in the Computer Science Department at Purdue, advised by Prof. Jean Honorio. My research focuses on developing statistically and computationally efficient algorithms with provable guarantees in the field of structured prediction, community detection, and related applications.

Previously I obtained my B.S. degree in Computer Science from University of Rochester, where I was advised by Dr. Ji Liu.

Publications

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

Professional Service

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