| Speeding Up Distributed Machine Learning Using Codes K Lee, M Lam, R Pedarsani, D Papailiopoulos, K Ramchandran IEEE Transactions on Information Theory, 1-1, 2017 | 1061 | 2017 |
| Attack of the tails: Yes, you really can backdoor federated learning H Wang, K Sreenivasan, S Rajput, H Vishwakarma, S Agarwal, J Sohn, ... NeurIPS 2020, 2020 | 959 | 2020 |
| DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models Y Fan, O Watkins, Y Du, H Liu, M Ryu, C Boutilier, P Abbeel, ... NeurIPS 2023, 2023 | 509* | 2023 |
| High-dimensional coded matrix multiplication K Lee, C Suh, K Ramchandran IEEE ISIT 2017, 2418-2422, 2017 | 277 | 2017 |
| When Do Redundant Requests Reduce Latency? NB Shah, K Lee, K Ramchandran IEEE Transactions on Communications 64 (2), 715-722, 2015 | 261 | 2015 |
| Gradient Inversion with Generative Image Prior J Kim, J Jeon, K Lee, S Oh, J Ok NeurIPS 2021, 2021 | 244* | 2021 |
| LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks T Dinh, Y Zeng, R Zhang, Z Lin, S Rajput, M Gira, J Sohn, ... NeurIPS 2022, 2022 | 215 | 2022 |
| FairBatch: Batch Selection for Model Fairness Y Roh, K Lee, SE Whang, C Suh ICLR 2021, 2021 | 207 | 2021 |
| Looped Transformers as Programmable Computers A Giannou, S Rajput, J Sohn, K Lee, JD Lee, D Papailiopoulos ICML 2023, 2023 | 188 | 2023 |
| The MDS Queue: Analysing the Latency Performance of Erasure Codes K Lee, NB Shah, L Huang, K Ramchandran IEEE Transactions on Information Theory 63 (5), 2822-2842, 2017 | 173* | 2017 |
| Teaching Arithmetic to Small Transformers N Lee, K Sreenivasan, JD Lee, K Lee, D Papailiopoulos ICLR 2024, 2024 | 158 | 2024 |
| Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks J Park, J Park, Z Xiong, N Lee, J Cho, S Oymak, K Lee, D Papailiopoulos ICML 2024, 2024 | 131 | 2024 |
| FR-Train: A mutual information-based approach to fair and robust training Y Roh, K Lee, SE Whang, C Suh ICML 2020, 2020 | 114 | 2020 |
| The Expressive Power of Low-Rank Adaptation Y Zeng, K Lee ICLR 2024, 2024 | 113 | 2024 |
| Improving Fairness via Federated Learning Y Zeng, H Chen, K Lee arXiv preprint arXiv:2110.15545, 2021 | 105 | 2021 |
| Prompted LLMs as Chatbot Modules for Long Open-domain Conversation G Lee, V Hartmann, J Park, D Papailiopoulos, K Lee Findings of ACL 2023, 2023 | 102 | 2023 |
| Optimizing DDPM Sampling with Shortcut Fine-Tuning Y Fan, K Lee ICML 2023, 2023 | 98 | 2023 |
| SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing based on Sparse-Graph Codes K Lee, R Pedarsani, K Ramchandran IEEE Transactions on Signal Processing, 2019 | 98 | 2019 |
| Hierarchical Coding for Distributed Computing H Park, K Lee, J Sohn, C Suh, J Moon IEEE ISIT 2018, 2018 | 90 | 2018 |
| Sample Selection for Fair and Robust Training Y Roh, K Lee, SE Whang, C Suh NeurIPS 2021, 2021 | 84 | 2021 |
Dimitris PapailiopoulosResearcher at Microsoft Research & Assoc. Professor at University of WisconsinVerified email at papail.io
