| Attack of the tails: Yes, you really can backdoor federated learning H Wang, K Sreenivasan, S Rajput, H Vishwakarma, S Agarwal, J Sohn, ... Advances in Neural Information Processing Systems (NeurIPS), 2020 | 705 | 2020 |
| DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation S Rajput, H Wang, Z Charles, D Papailiopoulos Advances in Neural Information Processing Systems (NeurIPS), 2019 | 141 | 2019 |
| Lift: Language-interfaced fine-tuning for non-language machine learning tasks T Dinh, Y Zeng, R Zhang, Z Lin, M Gira, S Rajput, J Sohn, ... Advances in Neural Information Processing Systems (NeurIPS), 2022 | 133 | 2022 |
| Recommender Systems with Generative Retrieval S Rajput, N Mehta, A Singh, R Keshavan, T Vu, L Heldt, L Hong, Y Tay, ... Advances in Neural Information Processing Systems (NeurIPS), 2023 | 131 | 2023 |
| Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient A Pensia, S Rajput, A Nagle, H Vishwakarma, D Papailiopoulos Advances in Neural Information Processing Systems (NeurIPS), 2020 | 115 | 2020 |
| Looped Transformers as Programmable Computers A Giannou, S Rajput, J Sohn, K Lee, JD Lee, D Papailiopoulos International Conference on Machine Learning (ICML), 2023 | 92 | 2023 |
| Closing the convergence gap of SGD without replacement S Rajput, A Gupta, D Papailiopoulos International Conference on Machine Learning (ICML), 2020 | 70 | 2020 |
| Does data augmentation lead to positive margin? S Rajput, Z Feng, Z Charles, PL Loh, D Papailiopoulos International Conference on Machine Learning (ICML), 2019 | 46 | 2019 |
| Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond C Yun, S Rajput, S Sra International Conference on Learning Representations (ICLR), 2022 | 45 | 2022 |
| Convergence and Margin of Adversarial Training on Separable Data Z Charles, S Rajput, S Wright, D Papailiopoulos arXiv preprint arXiv:1905.09209, 2019 | 22 | 2019 |
| Permutation-Based SGD: Is Random Optimal? S Rajput, K Lee, D Papailiopoulos International Conference on Learning Representations (ICLR), 2022 | 19 | 2022 |
| An exponential improvement on the memorization capacity of deep threshold networks S Rajput, K Sreenivasan, D Papailiopoulos, A Karbasi Advances in Neural Information Processing Systems (NeurIPS), 2021 | 19 | 2021 |
| Finding everything within random binary networks K Sreenivasan, S Rajput, J Sohn, D Papailiopoulos International Conference on Artificial Intelligence and Statistics (AISTATS), 2022 | 17* | 2022 |
| H. Chi, and Maheswaran Sathiamoorthy. 2023. Recommender systems with generative retrieval S Rajput, N Mehta, A Singh, RH Keshavan, T Vu, L Heldt, L Hong, Y Tay, ... arXiv preprint arXiv:2305.05065, 0 | 16 | |
| The Expressive Power of Tuning Only the Normalization Layers A Giannou, S Rajput, D Papailiopoulos The Thirty Sixth Annual Conference on Learning Theory, 4130-4131, 2023 | 10 | 2023 |
| The Expressive Power of Tuning Only the Norm Layers A Giannou, S Rajput, D Papailiopoulos Conference on Learning Theory (COLT), 2023 | 7 | 2023 |
| Maestro: Uncovering Low-Rank Structures via Trainable Decomposition S Horváth, S Laskaridis, S Rajput, H Wang arXiv preprint arXiv:2308.14929, 2023 | 3 | 2023 |
| Inference-Friendly Models With MixAttention S Rajput, Y Sheng, S Owen, V Chiley arXiv preprint arXiv:2409.15012, 2024 | 2 | 2024 |
| Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment T Dinh, J Sohn, S Rajput, T Ossowski, Y Ming, J Hu, D Papailiopoulos, ... EMNLP (Findings), 2022 | 1 | 2022 |
| Large-Scale SGD Algorithms and the Expressive Power of Modern Neural Networks S Rajput The University of Wisconsin-Madison, 2023 | | 2023 |
Dimitris PapailiopoulosResearcher at Microsoft Research & Assoc. Professor at University of Wisconsin在 papail.io 的电子邮件经过验证