Pranay Sharma - RankMe

55 papers A* 9A 4C 1Misc 4Journal 32Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Natural Policy Gradient for Average Reward Non-Stationary Reinforcement Learning. Trans. Mach. Learn. Res. Neharika Jali, Eshika Pathak, Pranay Sharma, Guannan Qu, Gauri Joshi
2025	—	`conf`	A Surrogate-Assisted Co-Evolutionary Framework for Bilevel Optimization. IJCCI (2) Sanup Araballi, Venkata Gandikota, Pranay Sharma, Prashant Khanduri, Chilukuri K. Mohan
2025	A*	`conf`	Debiasing Federated Learning with Correlated Client Participation. ICLR Zhenyu Sun, Ziyang Zhang, Zheng Xu, Gauri Joshi, Pranay Sharma, Ermin Wei
2025	A	`conf`	Federated Communication-Efficient Multi-Objective Optimization. AISTATS Baris Askin, Pranay Sharma, Gauri Joshi, Carlee Joe-Wong
2025	A	`conf`	High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent under Heavy-tailed Noise. AISTATS Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar
2025	J	`jnl`	Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning. CoRR Divyansh Jhunjhunwala, Pranay Sharma, Zheng Xu, Gauri Joshi
2025	J	`jnl`	Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning. Trans. Mach. Learn. Res. Divyansh Jhunjhunwala, Pranay Sharma, Zheng Xu, Gauri Joshi
2025	J	`jnl`	Natural Policy Gradient for Average Reward Non-Stationary RL. CoRR Neharika Jali, Eshika Pathak, Pranay Sharma, Guannan Qu, Gauri Joshi
2025	Misc	`conf`	On Decentralized Learning with Stochastic Subspace Descent. ICASSP Shivangi Dubey Sharma, Pranay Sharma, Ketan Rajawat
2025	J	`jnl`	The Cost of Shuffling in Private Gradient Based Optimization. CoRR Shuli Jiang, Pranay Sharma, Zhiwei Steven Wu, Gauri Joshi
2024	J	`jnl`	Debiasing Federated Learning with Correlated Client Participation. CoRR Zhenyu Sun, Ziyang Zhang, Zheng Xu, Gauri Joshi, Pranay Sharma, Ermin Wei
2024	A	`conf`	FedAST: Federated Asynchronous Simultaneous Training. UAI Baris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi
2024	J	`jnl`	FedAST: Federated Asynchronous Simultaneous Training. CoRR Baris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi
2024	J	`jnl`	Federated Communication-Efficient Multi-Objective Optimization. CoRR Baris Askin, Pranay Sharma, Gauri Joshi, Carlee Joe-Wong
2024	J	`jnl`	Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees. CoRR Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar
2024	Misc	`conf`	On Improved Distributed Random Reshuffling over Networks. ICASSP Pranay Sharma, Jiarui Li, Gauri Joshi
2023	A*	`conf`	Correlation Aware Sparsified Mean Estimation Using Random Projection. NeurIPS Shuli Jiang, Pranay Sharma, Gauri Joshi
2023	J	`jnl`	Correlation Aware Sparsified Mean Estimation Using Random Projection. CoRR Shuli Jiang, Pranay Sharma, Gauri Joshi
2023	J	`jnl`	Federated Minimax Optimization with Client Heterogeneity. CoRR Pranay Sharma, Rohan Panda, Gauri Joshi
2023	J	`jnl`	Federated Minimax Optimization with Client Heterogeneity. Trans. Mach. Learn. Res. Pranay Sharma, Rohan Panda, Gauri Joshi
2023	J	`jnl`	Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation. CoRR Davoud Ataee Tarzanagh, Mingchen Li, Pranay Sharma, Samet Oymak
2023	J	`jnl`	High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise. CoRR Aleksandar Armacki, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar
2023	J	`jnl`	Model Sparsification Can Simplify Machine Unlearning. CoRR Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
2023	A*	`conf`	Model Sparsity Can Simplify Machine Unlearning. NeurIPS Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
2023	A*	`conf`	On the Convergence of Federated Averaging with Cyclic Client Participation. ICML Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang
2023	J	`jnl`	On the Convergence of Federated Averaging with Cyclic Client Participation. CoRR Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang
2023	A*	`conf`	What Is Missing in IRM Training and Evaluation? Challenges and Solutions. ICLR Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu
2023	J	`jnl`	What Is Missing in IRM Training and Evaluation? Challenges and Solutions. CoRR Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu
2022	J	`jnl`	FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning. CoRR Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi
2022	A*	`conf`	Federated Minimax Optimization: Improved Convergence Analyses and Algorithms. ICML Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney
2022	J	`jnl`	Federated Minimax Optimization: Improved Convergence Analyses and Algorithms. CoRR Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney
2022	A*	`conf`	Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. ICML Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri
2022	J	`jnl`	Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. CoRR Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri
2022	A	`conf`	Fedvarp: Tackling the variance due to partial client participation in federated learning. UAI Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi
2021	J	`jnl`	Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations. IEEE Trans. Signal Inf. Process. over Networks Saikiran Bulusu, Prashant Khanduri, Swatantra Kafle, Pranay Sharma, Pramod K. Varshney
2021	—	`conf`	On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit. ACSCC Pranay Sharma, Prashant Khanduri, Lixin Shen, Donald J. Bucci, Pramod K. Varshney
2021	A*	`conf`	STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. NeurIPS Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney
2021	J	`jnl`	STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. CoRR Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney
2020	—	`conf`	Application of IoT and Machine Learning for Real-time Driver Monitoring and Assisting Device. ICCCNT Pranay Sharma, Naveksha Sood
2020	J	`jnl`	Communication Network Topology Inference via Transfer Entropy. IEEE Trans. Netw. Sci. Eng. Pranay Sharma, Donald J. Bucci, Swastik K. Brahma, Pramod K. Varshney
2020	J	`jnl`	Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction. CoRR Prashant Khanduri, Pranay Sharma, Swatantra Kafle, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney
2020	J	`jnl`	On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit. CoRR Pranay Sharma, Prashant Khanduri, Lixin Shen, Donald J. Bucci Jr., Pramod K. Varshney
2020	Misc	`conf`	On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines. ICASSP Saikiran Bulusu, Prashant Khanduri, Pranay Sharma, Pramod K. Varshney
2020	J	`jnl`	Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework. CoRR Pranay Sharma, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Xue Lin, Pramod K. Varshney
2019	J	`jnl`	Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations. CoRR Prashant Khanduri, Saikiran Bulusu, Pranay Sharma, Pramod K. Varshney
2019	J	`jnl`	Decentralized Gaussian Filters for Cooperative Self-Localization and Multi-Target Tracking. IEEE Trans. Signal Process. Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney
2019	C	`conf`	On Decentralized Self-localization and Tracking Under Measurement Origin Uncertainty. FUSION Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney
2019	J	`jnl`	Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity. CoRR Pranay Sharma, Prashant Khanduri, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney
2018	Misc	`conf`	On Self-Localization and Tracking with an Unknown Number of Targets. ACSSC Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney
2018	J	`jnl`	Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory. CoRR Kush R. Varshney, Prashant Khanduri, Pranay Sharma, Shan Zhang, Pramod K. Varshney
2013	—	`conf`	A lane-level dynamic traffic control system for driving efficiency optimization based on vehicular networks. PerCom Workshops Lien-Wu Chen, Chia-Chen Chang, Pranay Sharma, Jen-Hsiang Cheng, Chien-Cheng Wu, Yu-Chee Tseng
2013	J	`jnl`	Dynamic Traffic Control with Fairness and Throughput Optimization Using Vehicular Communications. IEEE J. Sel. Areas Commun. Lien-Wu Chen, Pranay Sharma, Yu-Chee Tseng
2012	J	`jnl`	A dynamic password-based user authentication scheme for hierarchical wireless sensor networks. J. Netw. Comput. Appl. Ashok Kumar Das, Pranay Sharma, Santanu Chatterjee, Jamuna Kanta Sing
2011	A*	`conf`	Eco-Sign: a load-based traffic light control system for environmental protection with vehicular communications. SIGCOMM Lien-Wu Chen, Pranay Sharma, Yu-Chee Tseng
2011	—	`conf`	On noise-enhanced distributed inference in the presence of Byzantines. Allerton Mukul Gagrani, Pranay Sharma, Satish G. Iyengar, V. Sriram Siddhardh Nadendla, Aditya Vempaty, Hao Chen, Pramod K. Varshney