Pranay Sharma
Pranay Sharma
Postdoctoral Researcher, Carnegie Mellon University
Подтвержден адрес электронной почты в домене andrew.cmu.edu - Главная страница
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
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
Communication Network Topology Inference via Transfer Entropy
P Sharma, DJ Bucci, SK Brahma, PK Varshney
IEEE Transactions on Network Science and Engineering, 2019
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
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
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
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
Byzantine resilient non-convex SVRG with distributed batch gradient computations
P Khanduri, S Bulusu, P Sharma, PK Varshney
arXiv preprint arXiv:1912.04531, 2019
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms
P Sharma, R Panda, G Joshi, PK Varshney
International Conference on Machine Learning, 19683-19730, 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
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
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling
S Khodadadian, P Sharma, G Joshi, ST Maguluri
International Conference on Machine Learning, 10997-11057, 2022
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
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
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
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
Zeroth-order hybrid gradient descent: Towards a principled black-box optimization framework
P Sharma, K Xu, S Liu, PY Chen, X Lin, PK Varshney
arXiv preprint arXiv:2012.11518, 2020
Federated Minimax Optimization with Client Heterogeneity
P Sharma, R Panda, G Joshi
arXiv preprint arXiv:2302.04249, 2023
On the Convergence of Federated Averaging with Cyclic Client Participation
YJ Cho, P Sharma, G Joshi, Z Xu, S Kale, T Zhang
arXiv preprint arXiv:2302.03109, 2023
Distributed Estimation in Large Scale Wireless Sensor Networks via a Two Step Group-based Approach
S Zhang, P Sharma, B Geng, PK Varshney
arXiv preprint arXiv:2203.09567, 2022
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