| Fedscale: Benchmarking model and system performance of federated learning at scale F Lai, Y Dai, S Singapuram, J Liu, X Zhu, H Madhyastha, M Chowdhury International conference on machine learning, 11814-11827, 2022 | 157 | 2022 |
| Astra: Exploiting predictability to optimize deep learning M Sivathanu, T Chugh, SS Singapuram, L Zhou Proceedings of the Twenty-Fourth International Conference on Architectural …, 2019 | 56 | 2019 |
| Flamingo: A User-Centric System for Fast and Energy-Efficient DNN Training on Smartphones SSV Singapuram, C Hu, F Lai, C Zhang, M Chowdhury Proceedings of the 4th International Workshop on Distributed Machine …, 2023 | 5* | 2023 |
| Avmaestro: A centralized policy enforcement framework for safe autonomous-driving environments Z Zhang, SSV Singapuram, Q Zhang, DK Hong, B Nguyen, ZM Mao, ... 2022 IEEE Intelligent Vehicles Symposium (IV), 1333-1339, 2022 | 3 | 2022 |
| Automatic Feature Isolation in Network Protocol Software Implementations Z Zhang, Q Zhang, B Nguyen, SSV Singapuram, ZM Mao, S Mahlke Proceedings of the 2020 ACM Workshop on Forming an Ecosystem Around Software …, 2020 | 1 | 2020 |
| Applied Reconfigurable Computing: 12th International Symposium, ARC 2016 Mangaratiba, RJ, Brazil, March 22–24, 2016 Proceedings V Bonato, C Bouganis, M Gorgon Springer, 2016 | 1 | 2016 |
| Performance Evaluation of Feed-Forward Backpropagation Neural Network for Classification on a Reconfigurable Hardware Architecture M Mohammadi, R Ronge, SS Singapuram, SK Nandy Applied Reconfigurable Computing: 12th International Symposium, ARC 2016 …, 2016 | 1 | 2016 |
| Enabling Julia to target GPGPUs using Polly SS Srivallabh https://summerofcode.withgoogle.com/archive/2017/projects/4839028788559872/, 2017 | | 2017 |
| 2.5-PC: A Faster and Non-Blocking Atomic Commit Protocol A Berding, SSV Singapuram, D Svoboda | | |
Lidong ZhouMicrosoft ResearchVerified email at microsoft.com
