Lin, Chi-Heng

13 publications

TMLR 2026 ToMoE: Converting Dense Large Language Models to Mixture-of-Experts Through Dynamic Structural Pruning Shangqian Gao, Ting Hua, Reza Shirkavand, Chi-Heng Lin, Zheng Tang, Zhengao Li, Longge Yuan, Fangyi Li, Zeyu Zhang, Alireza Ganjdanesh, Qian Lou, Jie Xu, Yen-Chang Hsu

ICLR 2025 MoDeGPT: Modular Decomposition for Large Language Model Compression Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu

ICML 2024 Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance Chiraag Kaushik, Ran Liu, Chi-Heng Lin, Amrit Khera, Matthew Y Jin, Wenrui Ma, Vidya Muthukumar, Eva L Dyer

NeurIPS 2024 DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models Shangqian Gao, Chi-Heng Lin, Ting Hua, Tang Zheng, Yilin Shen, Hongxia Jin, Yen-Chang Hsu

JMLR 2024 The Good, the Bad and the Ugly Sides of Data Augmentation: An Implicit Spectral Regularization Perspective Chi-Heng Lin, Chiraag Kaushik, Eva L. Dyer, Vidya Muthukumar

NeurIPS 2024 Your Contrastive Learning Problem Is Secretly a Distribution Alignment Problem Zihao Chen, Chi-Heng Lin, Ran Liu, Jingyun Xiao, Eva L. Dyer

ICML 2023 Half-Hop: A Graph Upsampling Approach for Slowing Down Message Passing Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Veličković, Eva L Dyer

ICML 2022 Provable Acceleration of Heavy Ball Beyond Quadratics for a Class of Polyak-Lojasiewicz Functions When the Non-Convexity Is Averaged-Out Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu

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

UAI 2021 Bayesian Optimization for Modular Black-Box Systems with Switching Costs Chi-Heng Lin, Joseph D. Miano, Eva L. Dyer

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

ICML 2021 Making Transport More Robust and Interpretable by Moving Data Through a Small Number of Anchor Points Chi-Heng Lin, Mehdi Azabou, Eva Dyer

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