| Mine your own view: A self-supervised approach for learning representations of neural activity M Azabou, MG Azar, R Liu, CH Lin, EC Johnson, K Bhaskaran-Nair, ... | 43* | |
| Drop, swap, and generate: A self-supervised approach for generating neural activity R Liu, M Azabou, M Dabagia, CH Lin, M Gheshlaghi Azar, K Hengen, ... Advances in neural information processing systems 34, 10587-10599, 2021 | 30* | 2021 |
| A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network JK Wang, CH Lin, J Abernethy International Conference on Machine Learning (ICML) 2021, 2021 | 22 | 2021 |
| Escaping saddle points faster with stochastic momentum JK Wang, CH Lin, J Abernethy International Conference on Learning Representations (ICLR) 2020, 2020 | 19 | 2020 |
| Provable acceleration of heavy ball beyond quadratics for a class of Polyak-Lojasiewicz functions when the non-convexity is averaged-out JK Wang, CH Lin, A Wibisono, B Hu International conference on machine learning, 22839-22864, 2022 | 17 | 2022 |
| Making transport more robust and interpretable by moving data through a small number of anchor points CH Lin, M Azabou, EL Dyer International Conference on Machine Learning (ICML) 2021, 2021 | 15 | 2021 |
| Efficient error-resilient multicasting for multi-view 3D videos in wireless network CH Lin, DN Yang, JT Lee, W Liao 2016 IEEE Global Communications Conference (GLOBECOM), 1-7, 2016 | 11 | 2016 |
| The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective CH Lin, C Kaushik, EL Dyer, V Muthukumar Journal of Machine Learning Research, 2024 | 10 | 2024 |
| Half-Hop: A graph upsampling approach for slowing down message passing M Azabou, V Ganesh, S Thakoor, CH Lin, L Sathidevi, R Liu, M Valko, ... ICML 2023, 2023 | 6 | 2023 |
| In-network computations of machine-to-machine communications for wireless robotics FM Tseng, CH Lin, KC Chen Wireless personal communications 70 (3), 1097-1119, 2013 | 6 | 2013 |
| Using self-supervision and augmentations to build insights into neural coding M Azabou, M Dabagia, R Liu, CH Lin, KB Hengen, WUS Louis, EL Dyer Proceedings of Workshop on Self-Supervised Learning-Theory and Practice on …, 2021 | 2 | 2021 |
| Bayesian optimization for modular black-box systems with switching costs CH Lin, JD Miano, EL Dyer Uncertainty in Artificial Intelligence (UAI) 2021, 2021 | 2 | 2021 |
| Multicast Group Management for Multi-View 3D Videos in Wireless Networks CH Lin, DN Yang, CC Lin, W Liao arXiv preprint arXiv:1409.8352, 2014 | 1 | 2014 |
| DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling HJ Shikhar Tuli, Chi-Heng Lin, Yen-Chang Hsu, Niraj Jha, Yilin Shen NAACL, 2024 | | 2024 |
| SLiM: Speculative Decoding with Hypothesis Reduction HJ Chi-Heng Lin, Shikhar Tuli, James Seale Smith, Yen-Chang Hsu, Yilin Shen NAACL findings, 2024 | | 2024 |
| Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance C Kaushik, R Liu, CH Lin, A Khera, MY Jin, W Ma, V Muthukumar, EL Dyer arXiv preprint arXiv:2402.11742, 2024 | | 2024 |
| Understanding Data Manipulation and How to Leverage it To Improve Generalization CH Lin Georgia Institute of Technology, 2022 | | 2022 |
| Downlink Linear Precoders Based on Statistical CSI for Multicell MIMO-OFDM E Baktash, CH Lin, X Wang, M Karimi Wireless Communications and Mobile Computing 2017, 2017 | | 2017 |
| Error-Resilient Multicasting for Multi-View 3D Videos in IEEE 802.11 Networks CH Lin, DN Yang, JT Lee, W Liao arXiv preprint arXiv:1503.08726, 2015 | | 2015 |
Eva L. DyerGeorgia Institute of TechnologyVerified email at gatech.edu
