| 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 33, 16070-16084, 2020 | 134 | 2020 |
| Adaptive Gradient Communication via Critical Learning Regime Identification S Agarwal, H Wang, K Lee, S Venkataraman, D Papailiopoulos Proceedings of Machine Learning and Systems 3, 55-80, 2021 | 11 | 2021 |
| On the utility of gradient compression in distributed training systems S Agarwal, H Wang, S Venkataraman, D Papailiopoulos Proceedings of Machine Learning and Systems 4, 652-672, 2022 | 10 | 2022 |
| Pufferfish: Communication-efficient models at no extra cost H Wang, S Agarwal, D Papailiopoulos Proceedings of Machine Learning and Systems 3, 365-386, 2021 | 9 | 2021 |
| AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning Y Liu, S Agarwal, S Venkataraman arXiv preprint arXiv:2102.01386, 2021 | 6 | 2021 |
| BagPipe: Accelerating Deep Recommendation Model Training S Agarwal, Z Zhang, S Venkataraman arXiv preprint arXiv:2202.12429, 2022 | | 2022 |
| Method and system for efficient clustering of combined numeric and qualitative data records S Agarwal, B Aravindakshan, B Sudarshan, H Chandrasekaran US Patent 10,846,311, 2020 | | 2020 |
| Scalable K-Medoids via True Error Bound and Familywise Bandits A Babu, S Agarwal, S Babu, H Chandrasekaran arXiv preprint arXiv:1905.10979, 2019 | | 2019 |
