| Reducing duplicate filters in deep neural networks A RoyChowdhury, P Sharma, E Learned-Miller, A Roy NIPS workshop on deep learning: Bridging theory and practice 1 (2), 6, 2017 | 46 | 2017 |
| A model-free approach to meta-level control of anytime algorithms J Svegliato, P Sharma, S Zilberstein 2020 IEEE International Conference on Robotics and Automation (ICRA), 11436 …, 2020 | 20 | 2020 |
| PROSPER: Extracting Protocol Specifications Using Large Language Models P Sharma, V Yegneswaran Proceedings of the 22nd ACM Workshop on Hot Topics in Networks, 41-47, 2023 | 15 | 2023 |
| Scalable microservice forensics and stability assessment using variational autoencoders P Sharma, P Porras, S Cheung, J Carpenter, V Yegneswaran arXiv preprint arXiv:2104.13193, 2021 | 4 | 2021 |
| 6G-XSec: Explainable Edge Security for Emerging OpenRAN Architectures H Wen, P Sharma, V Yegneswaran, P Porras, A Gehani, Z Lin Proceedings of the 23rd ACM Workshop on Hot Topics in Networks, 77-85, 2024 | | 2024 |
| Methods, apparatuses and systems for providing forensics to manage containers PA Porras, P Sharma US Patent 11,586,521, 2023 | | 2023 |
| A Model-Free Approach to Meta-Level Control of Anytime Planning J Svegliato, P Sharma, S Zilberstein | | |
| EIReLaND: Evaluating and Interpreting Reinforcement-Learning-based Network Defenses S Cheung, J Claypoole, P Sharma, V Yegneswaran, A Gehani, S Jha, ... | | |
