| A near-optimal algorithm for stochastic bilevel optimization via double-momentum P Khanduri, S Zeng, M Hong, HT Wai, Z Wang, Z Yang Advances in Neural Information Processing Systems 34, 30271-30283, 2021 | 120 | 2021 |
| Revisiting and advancing fast adversarial training through the lens of bi-level optimization Y Zhang, G Zhang, P Khanduri, M Hong, S Chang, S Liu International Conference on Machine Learning, 26693-26712, 2022 | 73 | 2022 |
| STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning P Khanduri, P Sharma, H Yang, M Hong, J Liu, K Rajawat, PK Varshney Advances in Neural Information Processing Systems 34, 6050-6061, 2021 | 64 | 2021 |
| Anarchic federated learning H Yang, X Zhang, P Khanduri, J Liu International Conference on Machine Learning, 25331-25363, 2022 | 63 | 2022 |
| Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory KR Varshney, P Khanduri, P Sharma, S Zhang, PK Varshney arXiv preprint arXiv:1806.09710, 2018 | 24 | 2018 |
| On distributed online convex optimization with sublinear dynamic regret and fit P Sharma, P Khanduri, L Shen, DJ Bucci, PK Varshney 2021 55th Asilomar Conference on Signals, Systems, and Computers, 1013-1017, 2021 | 22 | 2021 |
| Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations S Bulusu, P Khanduri, S Kafle, P Sharma, PK Varshney IEEE Transactions on Signal and Information Processing over Networks 7, 754-766, 2021 | 16* | 2021 |
| Parallel Restarted SPIDER--Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity P Sharma, S Kafle, P Khanduri, S Bulusu, K Rajawat, PK Varshney arXiv preprint arXiv:1912.06036, 2019 | 16 | 2019 |
| Distributed Sequential Detection: Dependent Observations and Imperfect Communication S Zhang, P Khanduri, PK Varshney IEEE Transactions on Signal Processing 68, 830-842, 2019 | 16 | 2019 |
| Auto-Prompting SAM for Mobile Friendly 3D Medical Image Segmentation C Li, P Khanduri, Y Qiang, RI Sultan, I Chetty, D Zhu arXiv preprint arXiv:2308.14936, 2023 | 15 | 2023 |
| An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning Y Zhang, P Khanduri, I Tsaknakis, Y Yao, M Hong, S Liu arXiv preprint arXiv:2308.00788, 2023 | 15 | 2023 |
| An Implicit Gradient-Type Method for Linearly Constrained Bilevel Problems I Tsaknakis, P Khanduri, M Hong ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 13 | 2022 |
| A momentum-assisted single-timescale stochastic approximation algorithm for bilevel optimization P Khanduri, S Zeng, M Hong, HT Wai, Z Wang, Z Yang arXiv preprint arXiv:2102.07367, 2021 | 12 | 2021 |
| Sequential random distortion testing of non-stationary processes P Khanduri, D Pastor, V Sharma, PK Varshney IEEE Transactions on Signal Processing 67 (21), 5450-5462, 2019 | 12 | 2019 |
| INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks Z Liu, X Zhang, P Khanduri, S Lu, J Liu Proceedings of the Twenty-Third International Symposium on Theory …, 2022 | 11 | 2022 |
| On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines S Bulusu, P Khanduri, P Sharma, PK Varshney ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 10 | 2020 |
| Truncated sequential non-parametric hypothesis testing based on random distortion testing P Khanduri, D Pastor, V Sharma, PK Varshney IEEE Transactions on Signal Processing 67 (15), 4027-4042, 2019 | 10 | 2019 |
| Linearly constrained bilevel optimization: A smoothed implicit gradient approach P Khanduri, I Tsaknakis, Y Zhang, J Liu, S Liu, J Zhang, M Hong International Conference on Machine Learning, 2023 | 9 | 2023 |
| Joint collaboration and compression design for distributed sequential estimation in a wireless sensor network X Cheng, P Khanduri, B Chen, PK Varshney IEEE Transactions on Signal Processing 69, 5448-5462, 2021 | 9 | 2021 |
| Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach," in Proc. ICLR, Virtual Event, April 2022 P Khanduri, H Yang, M Hong, J Liu, H Wai, S Liu Proc. ICLR, 2022 | 6 | 2022 |
Pramod VarshneyDistinguished Professor of EECS, Syracuse University在 syr.edu 的电子邮件经过验证
