Chi-Heng Lin

ECE Ph.D. student

Georgia Institute of Technology

Biography

Chi-Heng is an ECE PhD student in the NerDS Lab at GeorgiaTech, lead by Dr. Eva L Dyer. His research interests include Computational Neuroscience, Deep Learning, and Bayesian Statistics. An unknown reason connects him with 寶貓.

Interests

Computational Neuroscience
Deep Learning
Bayesian Statistics

Education

PhD in Electrical and Computer Engineering
Georgia Institute of Technology
M.A. in Statistics
Columbia University
B.S. & M.S. in Electrical Engineering
National Taiwan University

Recent Publications

Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer (2021). Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. NeurIPS 2021 (oral presentation).

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Chi-Heng Lin, Joseph D Miano, Eva L Dyer (2021). Bayesian optimization for modular black-box systems with switching costs. UAI 2021.

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Chi-Heng Lin, Mehdi Azabou, Eva L Dyer (2021). Making transport more robust and interpretable by moving data through a small number of anchor points. ICML 2021.

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Jun-Kun Wang, Chi-Heng Lin, Jacob Abernethy (2021). A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network. ICML 2021.

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Jun-Kun Wang, Chi-Heng Lin, Jacob Abernethy (2020). Escaping Saddle Points Faster with Stochastic Momentum. ICLR 2020.

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Projects

Low rank optimal transport

Understand Data Augmentation through Linear Models

Featured Publications

Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer

June 2021 NeurIPS 2021 (oral presentation)

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity

Chi-Heng Lin, Joseph D Miano, Eva L Dyer

May 2021 UAI 2021

Bayesian optimization for modular black-box systems with switching costs

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Chi-Heng Lin, Mehdi Azabou, Eva L Dyer

May 2021 ICML 2021