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Prashant Khanduri
Prashant Khanduri
Wayne State University
Подтвержден адрес электронной почты в домене wayne.edu - Главная страница
Название
Процитировано
Процитировано
Год
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
612021
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
arXiv preprint arXiv:2106.10435, 2021
29*2021
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
202018
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
172022
Anarchic federated learning
H Yang, X Zhang, P Khanduri, J Liu
International Conference on Machine Learning, 25331-25363, 2022
162022
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
142021
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
142019
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
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
122019
Distributed Sequential Detection: Dependent Observations and Imperfect Communication
S Zhang, P Khanduri, PK Varshney
IEEE Transactions on Signal Processing 68, 830-842, 2019
112019
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
92021
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
72020
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
62021
Online Design of Optimal Precoders for High Dimensional Signal Detection
P Khanduri, LN Theagarajan, PK Varshney
IEEE Transactions on Signal Processing 67 (15), 4122-4135, 2019
6*2019
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
52020
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
52019
On Random Distortion testing based sequential Non parametric Hypothesis Testing
P Khanduri, D Pastor, VK Sharma, PK Varshney
56th annual Allerton Conference on communication, control and computing, ., 2018
52018
Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach
P Khanduri, B Kailkhura, JJ Thiagarajan, PK Varshney
IEEE Signal Processing Letters, 2016
42016
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
32022
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach
P Khanduri, H Yang, M Hong, J Liu, HT Wai, S Liu
International Conference on Learning Representations, 2021
32021
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