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, P Varshney Advances in Neural Information Processing Systems 34, 6050-6061, 2021 | 65 | 2021 |
Decentralized Gaussian filters for cooperative self-localization and multi-target tracking P Sharma, AA Saucan, DJ Bucci, PK Varshney IEEE Transactions on Signal Processing 67 (22), 5896-5911, 2019 | 55 | 2019 |
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling S Khodadadian, P Sharma, G Joshi, ST Maguluri International Conference on Machine Learning, 10997-11057, 2022 | 50 | 2022 |
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms P Sharma, R Panda, G Joshi, PK Varshney International Conference on Machine Learning, 19683-19730, 2022 | 41 | 2022 |
Fedvarp: Tackling the variance due to partial client participation in federated learning D Jhunjhunwala, P Sharma, A Nagarkatti, G Joshi Uncertainty in Artificial Intelligence, 906-916, 2022 | 36 | 2022 |
Communication Network Topology Inference via Transfer Entropy P Sharma, DJ Bucci, SK Brahma, PK Varshney IEEE Transactions on Network Science and Engineering, 2019 | 35 | 2019 |
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 |
On noise-enhanced distributed inference in the presence of Byzantines M Gagrani, P Sharma, S Iyengar, VSS Nadendla, A Vempaty, H Chen, ... 2011 49th Annual Allerton Conference on Communication, Control, and …, 2011 | 20 | 2011 |
Model sparsification can simplify machine unlearning J Jia, J Liu, P Ram, Y Yao, G Liu, Y Liu, P Sharma, S Liu arXiv preprint arXiv:2304.04934, 2023 | 19 | 2023 |
Model sparsity can simplify machine unlearning J Liu, P Ram, Y Yao, G Liu, Y Liu, P SHARMA, S Liu Advances in Neural Information Processing Systems 36, 2024 | 16 | 2024 |
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 |
On the convergence of federated averaging with cyclic client participation YJ Cho, P Sharma, G Joshi, Z Xu, S Kale, T Zhang International Conference on Machine Learning, 5677-5721, 2023 | 15 | 2023 |
Byzantine resilient non-convex svrg with distributed batch gradient computations P Khanduri, S Bulusu, P Sharma, PK Varshney arXiv preprint arXiv:1912.04531, 2019 | 12 | 2019 |
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 |
Federated minimax optimization with client heterogeneity P Sharma, R Panda, G Joshi arXiv preprint arXiv:2302.04249, 2023 | 8 | 2023 |
What is missing in IRM training and evaluation? challenges and solutions Y Zhang, P Sharma, P Ram, M Hong, K Varshney, S Liu arXiv preprint arXiv:2303.02343, 2023 | 5 | 2023 |
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 | 4 | 2021 |
Distributed stochastic non-convex optimization: Momentum-based variance reduction P Khanduri, P Sharma, S Kafle, S Bulusu, K Rajawat, PK Varshney arXiv preprint arXiv:2005.00224, 2020 | 4 | 2020 |
On Self-Localization and Tracking with an Unknown Number of Targets P Sharma, AA Saucan, DJ Bucci, PK Varshney 2018 52nd Asilomar Conference on Signals, Systems, and Computers, 1735 - 1739, 2019 | 4 | 2019 |