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ORCIDPranay Sharma
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2020 – today
- 2024
[c17]Pranay Sharma, Jiarui Li, Gauri Joshi:
On Improved Distributed Random Reshuffling over Networks. ICASSP 2024: 13211-13215- [i21]Baris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi:
FedAST: Federated Asynchronous Simultaneous Training. CoRR abs/2406.00302 (2024) - [i20]Zhenyu Sun, Ziyang Zhang, Zheng Xu, Gauri Joshi, Pranay Sharma, Ermin Wei:
Debiasing Federated Learning with Correlated Client Participation. CoRR abs/2410.01209 (2024) - [i19]Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar:
Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees. CoRR abs/2410.13954 (2024) - [i18]Baris Askin, Pranay Sharma, Gauri Joshi, Carlee Joe-Wong:
Federated Communication-Efficient Multi-Objective Optimization. CoRR abs/2410.16398 (2024) - 2023
- [j6]Pranay Sharma, Rohan Panda, Gauri Joshi:
Federated Minimax Optimization with Client Heterogeneity. Trans. Mach. Learn. Res. 2023 (2023) - [c16]Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu:
What Is Missing in IRM Training and Evaluation? Challenges and Solutions. ICLR 2023 - [c15]Yae Jee Cho, Pranay Sharma
, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang:
On the Convergence of Federated Averaging with Cyclic Client Participation. ICML 2023: 5677-5721 - [c14]Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu:
Model Sparsity Can Simplify Machine Unlearning. NeurIPS 2023 - [c13]Shuli Jiang, Pranay Sharma, Gauri Joshi:
Correlation Aware Sparsified Mean Estimation Using Random Projection. NeurIPS 2023 - [i17]Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang:
On the Convergence of Federated Averaging with Cyclic Client Participation. CoRR abs/2302.03109 (2023) - [i16]Pranay Sharma, Rohan Panda, Gauri Joshi:
Federated Minimax Optimization with Client Heterogeneity. CoRR abs/2302.04249 (2023) - [i15]Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu:
What Is Missing in IRM Training and Evaluation? Challenges and Solutions. CoRR abs/2303.02343 (2023) - [i14]Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu:
Model Sparsification Can Simplify Machine Unlearning. CoRR abs/2304.04934 (2023) - [i13]Davoud Ataee Tarzanagh, Mingchen Li, Pranay Sharma, Samet Oymak:
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation. CoRR abs/2306.01648 (2023) - [i12]Aleksandar Armacki, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar:
High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise. CoRR abs/2310.18784 (2023) - [i11]Shuli Jiang, Pranay Sharma, Gauri Joshi:
Correlation Aware Sparsified Mean Estimation Using Random Projection. CoRR abs/2310.18868 (2023) - 2022
- [c12]Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri:
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. ICML 2022: 10997-11057 - [c11]Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney:
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms. ICML 2022: 19683-19730 - [c10]Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi:
Fedvarp: Tackling the variance due to partial client participation in federated learning. UAI 2022: 906-916 - [i10]Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney:
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms. CoRR abs/2203.04850 (2022) - [i9]Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri:
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. CoRR abs/2206.10185 (2022) - [i8]Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi:
FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning. CoRR abs/2207.14130 (2022) - 2021
- [j5]Saikiran Bulusu, Prashant Khanduri, Swatantra Kafle, Pranay Sharma, Pramod K. Varshney:
Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations. IEEE Trans. Signal Inf. Process. over Networks 7: 754-766 (2021) - [c9]Pranay Sharma, Prashant Khanduri, Lixin Shen, Donald J. Bucci, Pramod K. Varshney:
On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit. ACSCC 2021: 1013-1017 - [c8]Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney:
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. NeurIPS 2021: 6050-6061 - [i7]Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney:
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. CoRR abs/2106.10435 (2021) - 2020
- [j4]Pranay Sharma, Donald J. Bucci, Swastik K. Brahma, Pramod K. Varshney:
Communication Network Topology Inference via Transfer Entropy. IEEE Trans. Netw. Sci. Eng. 7(1): 562-575 (2020) - [c7]Saikiran Bulusu, Prashant Khanduri, Pranay Sharma, Pramod K. Varshney:
On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines. ICASSP 2020: 3137-3141 - [c6]Pranay Sharma, Naveksha Sood:
Application of IoT and Machine Learning for Real-time Driver Monitoring and Assisting Device. ICCCNT 2020: 1-7 - [i6]Pranay Sharma, Prashant Khanduri, Lixin Shen, Donald J. Bucci Jr., Pramod K. Varshney:
On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit. CoRR abs/2001.03166 (2020) - [i5]Prashant Khanduri, Pranay Sharma, Swatantra Kafle, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney:
Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction. CoRR abs/2005.00224 (2020) - [i4]Pranay Sharma, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Xue Lin, Pramod K. Varshney:
Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework. CoRR abs/2012.11518 (2020)
2010 – 2019
- 2019
- [j3]Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney:
Decentralized Gaussian Filters for Cooperative Self-Localization and Multi-Target Tracking. IEEE Trans. Signal Process. 67(22): 5896-5911 (2019) - [c5]Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney:
On Decentralized Self-localization and Tracking Under Measurement Origin Uncertainty. FUSION 2019: 1-8 - [i3]Prashant Khanduri, Saikiran Bulusu, Pranay Sharma, Pramod K. Varshney:
Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations. CoRR abs/1912.04531 (2019) - [i2]Pranay Sharma, Prashant Khanduri, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney:
Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity. CoRR abs/1912.06036 (2019) - 2018
- [c4]Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney:
On Self-Localization and Tracking with an Unknown Number of Targets. ACSSC 2018: 1735-1739 - [i1]Kush R. Varshney, Prashant Khanduri, Pranay Sharma, Shan Zhang, Pramod K. Varshney:
Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory. CoRR abs/1806.09710 (2018) - 2013
- [j2]Lien-Wu Chen, Pranay Sharma, Yu-Chee Tseng:
Dynamic Traffic Control with Fairness and Throughput Optimization Using Vehicular Communications. IEEE J. Sel. Areas Commun. 31(9-Supplement): 504-512 (2013) - [c3]Lien-Wu Chen, Chia-Chen Chang, Pranay Sharma, Jen-Hsiang Cheng, Chien-Cheng Wu, Yu-Chee Tseng:
A lane-level dynamic traffic control system for driving efficiency optimization based on vehicular networks. PerCom Workshops 2013: 297-299 - 2012
- [j1]Ashok Kumar Das, Pranay Sharma, Santanu Chatterjee, Jamuna Kanta Sing:
A dynamic password-based user authentication scheme for hierarchical wireless sensor networks. J. Netw. Comput. Appl. 35(5): 1646-1656 (2012) - 2011
- [c2]Mukul Gagrani, Pranay Sharma, Satish G. Iyengar, V. Sriram Siddhardh Nadendla, Aditya Vempaty, Hao Chen, Pramod K. Varshney:
On noise-enhanced distributed inference in the presence of Byzantines. Allerton 2011: 1222-1229 - [c1]Lien-Wu Chen, Pranay Sharma, Yu-Chee Tseng:
Eco-Sign: a load-based traffic light control system for environmental protection with vehicular communications. SIGCOMM 2011: 438-439
Coauthor Index
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