Pranay Sharma

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 36

Top Topics

Stochastic Gradient Descent

Machine Learning

Variance Reduction

Target Tracking

Top Venues

Publications

Baris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi
FedAST: Federated Asynchronous Simultaneous Training. CoRR (2024)
Pranay Sharma, Jiarui Li, Gauri Joshi
On Improved Distributed Random Reshuffling over Networks. ICASSP (2024)
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)
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 (2023)
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 (2023)
Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
Model Sparsification Can Simplify Machine Unlearning. CoRR (2023)
Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang
On the Convergence of Federated Averaging with Cyclic Client Participation. CoRR (2023)
Shuli Jiang, Pranay Sharma, Gauri Joshi
Correlation Aware Sparsified Mean Estimation Using Random Projection. NeurIPS (2023)
Pranay Sharma, Rohan Panda, Gauri Joshi
Federated Minimax Optimization with Client Heterogeneity. Trans. Mach. Learn. Res. 2023 (2023)
Shuli Jiang, Pranay Sharma, Gauri Joshi
Correlation Aware Sparsified Mean Estimation Using Random Projection. CoRR (2023)
Pranay Sharma, Rohan Panda, Gauri Joshi
Federated Minimax Optimization with Client Heterogeneity. CoRR (2023)
Davoud Ataee Tarzanagh, Mingchen Li, Pranay Sharma, Samet Oymak
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation. CoRR (2023)
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)
Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
Model Sparsity Can Simplify Machine Unlearning. NeurIPS (2023)
Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi
FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning. CoRR (2022)
Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms. ICML (2022)
Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. ICML (2022)
Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. CoRR (2022)
Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi
Fedvarp: Tackling the variance due to partial client participation in federated learning. UAI (2022)
Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms. CoRR (2022)
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 (2021)
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)
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)
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 (2021)
Prashant Khanduri, Pranay Sharma, Swatantra Kafle, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney
Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction. CoRR (2020)
Saikiran Bulusu, Prashant Khanduri, Pranay Sharma, Pramod K. Varshney
On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines. ICASSP (2020)
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 (2020)
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) (2020)
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 (2020)
Pranay Sharma, Naveksha Sood
Application of IoT and Machine Learning for Real-time Driver Monitoring and Assisting Device. ICCCNT (2020)
Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney
On Decentralized Self-localization and Tracking Under Measurement Origin Uncertainty. FUSION (2019)
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) (2019)
Pranay Sharma, Prashant Khanduri, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney
Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity. CoRR (2019)
Prashant Khanduri, Saikiran Bulusu, Pranay Sharma, Pramod K. Varshney
Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations. CoRR (2019)
Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci, Pramod K. Varshney
On Self-Localization and Tracking with an Unknown Number of Targets. ACSSC (2018)
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 (2018)
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) (2013)
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)
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) (2012)
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)
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)