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2020 – today
- 2024
[j3]Chi-Heng Lin, Chiraag Kaushik, Eva L. Dyer, Vidya Muthukumar:
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective. J. Mach. Learn. Res. 25: 91:1-91:85 (2024)- [c11]Chiraag Kaushik, Ran Liu, Chi-Heng Lin, Amrit Khera, Matthew Y. Jin, Wenrui Ma, Vidya Muthukumar, Eva L. Dyer:
Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance. ICML 2024 - [c10]Chi-Heng Lin, Shikhar Tuli, James Seale Smith, Yen-Chang Hsu, Yilin Shen, Hongxia Jin:
SLiM: Speculative Decoding with Hypothesis Reduction. NAACL-HLT (Findings) 2024: 1005-1017 - [c9]Shikhar Tuli, Chi-Heng Lin, Yen-Chang Hsu, Niraj K. Jha, Yilin Shen, Hongxia Jin:
DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling. NAACL-HLT 2024: 3322-3345 - [i12]Chiraag Kaushik, Ran Liu, Chi-Heng Lin, Amrit Khera, Matthew Y. Jin, Wenrui Ma, Vidya Muthukumar, Eva L. Dyer:
Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance. CoRR abs/2402.11742 (2024) - [i11]Shikhar Tuli, Chi-Heng Lin, Yen-Chang Hsu, Niraj K. Jha, Yilin Shen, Hongxia Jin:
DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling. CoRR abs/2405.00888 (2024) - [i10]Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu:
MoDeGPT: Modular Decomposition for Large Language Model Compression. CoRR abs/2408.09632 (2024) - 2023
- [b1]Chi-Heng Lin:
Understanding Data Manipulation and How to Leverage it To Improve Generalization. Georgia Institute of Technology, Atlanta, GA, USA, 2023 - [c8]Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Velickovic, Eva L. Dyer:
Half-Hop: A graph upsampling approach for slowing down message passing. ICML 2023: 1341-1360 - [i9]Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Velickovic, Eva L. Dyer:
Half-Hop: A graph upsampling approach for slowing down message passing. CoRR abs/2308.09198 (2023) - 2022
- [c7]Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu:
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out. ICML 2022: 22839-22864 - [i8]Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu:
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out. CoRR abs/2206.11872 (2022) - [i7]Chi-Heng Lin, Chiraag Kaushik, Eva L. Dyer, Vidya Muthukumar:
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective. CoRR abs/2210.05021 (2022) - 2021
- [c6]Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer:
Making transport more robust and interpretable by moving data through a small number of anchor points. ICML 2021: 6631-6641 - [c5]Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy:
A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network. ICML 2021: 10816-10827 - [c4]Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer:
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. NeurIPS 2021: 10587-10599 - [c3]Chi-Heng Lin, Joseph D. Miano, Eva L. Dyer:
Bayesian optimization for modular black-box systems with switching costs. UAI 2021: 1024-1034 - [i6]Mehdi Azabou, Mohammad Gheshlaghi Azar, Ran Liu, Chi-Heng Lin, Erik C. Johnson, Kiran Bhaskaran-Nair, Max Dabagia, Keith B. Hengen
, William R. Gray Roncal, Michal Valko, Eva L. Dyer:
Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction. CoRR abs/2102.10106 (2021) - [i5]Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy:
Escaping Saddle Points Faster with Stochastic Momentum. CoRR abs/2106.02985 (2021) - [i4]Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer:
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. CoRR abs/2111.02338 (2021) - 2020
- [c2]Jun-Kun Wang, Chi-Heng Lin, Jacob D. Abernethy:
Escaping Saddle Points Faster with Stochastic Momentum. ICLR 2020 - [i3]Chi-Heng Lin, Joseph D. Miano, Eva L. Dyer:
Bayesian optimization for modular black-box systems with switching costs. CoRR abs/2006.02624 (2020) - [i2]Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer:
Making transport more robust and interpretable by moving data through a small number of anchor points. CoRR abs/2012.11589 (2020)
2010 – 2019
- 2017
- [j2]Ebrahim Baktash, Chi-Heng Lin, Xiaodong Wang, Mahmood Karimi:
Downlink Linear Precoders Based on Statistical CSI for Multicell MIMO-OFDM. Wirel. Commun. Mob. Comput. 2017 (2017) - 2016
- [c1]Chi-Heng Lin, De-Nian Yang, Ji-Tang Lee, Wanjiun Liao:
Efficient Error-Resilient Multicasting for Multi-View 3D Videos in Wireless Network. GLOBECOM 2016: 1-7 - 2015
- [i1]Chi-Heng Lin, De-Nian Yang, Ji-Tang Lee, Wanjiun Liao:
Error-Resilient Multicast for Multi-View 3D Videos in IEEE 802.11 Networks. CoRR abs/1503.08726 (2015) - 2013
- [j1]Fan-Min Tseng, Chi-Heng Lin, Kwang-Cheng Chen:
In-Network Computations of Machine-to-Machine Communications for Wireless Robotics. Wirel. Pers. Commun. 70(3): 1097-1119 (2013)
Coauthor Index
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last updated on 2024-09-26 01:52 CEST by the dblp team
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