Pranay Sharma

Orcid: 0009-0007-8027-7913

According to our database1, Pranay Sharma authored at least 35 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Federated Communication-Efficient Multi-Objective Optimization.
CoRR, 2024

Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees.
CoRR, 2024

Debiasing Federated Learning with Correlated Client Participation.
CoRR, 2024

FedAST: Federated Asynchronous Simultaneous Training.
CoRR, 2024

On Improved Distributed Random Reshuffling over Networks.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Federated Minimax Optimization with Client Heterogeneity.
Trans. Mach. Learn. Res., 2023

High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise.
CoRR, 2023

Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation.
CoRR, 2023

Model Sparsification Can Simplify Machine Unlearning.
CoRR, 2023

Correlation Aware Sparsified Mean Estimation Using Random Projection.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Model Sparsity Can Simplify Machine Unlearning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Convergence of Federated Averaging with Cyclic Client Participation.
Proceedings of the International Conference on Machine Learning, 2023

What Is Missing in IRM Training and Evaluation? Challenges and Solutions.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Fedvarp: Tackling the variance due to partial client participation in federated learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Federated Minimax Optimization: Improved Convergence Analyses and Algorithms.
Proceedings of the International Conference on Machine Learning, 2022

Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling.
Proceedings of the International Conference on Machine Learning, 2022

2021
Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations.
IEEE Trans. Signal Inf. Process. over Networks, 2021

STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Communication Network Topology Inference via Transfer Entropy.
IEEE Trans. Netw. Sci. Eng., 2020

Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework.
CoRR, 2020

Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction.
CoRR, 2020

Application of IoT and Machine Learning for Real-time Driver Monitoring and Assisting Device.
Proceedings of the 11th International Conference on Computing, 2020

On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Decentralized Gaussian Filters for Cooperative Self-Localization and Multi-Target Tracking.
IEEE Trans. Signal Process., 2019

Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity.
CoRR, 2019

Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations.
CoRR, 2019

On Decentralized Self-localization and Tracking Under Measurement Origin Uncertainty.
Proceedings of the 22th International Conference on Information Fusion, 2019

2018
Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory.
CoRR, 2018

On Self-Localization and Tracking with an Unknown Number of Targets.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2013
Dynamic Traffic Control with Fairness and Throughput Optimization Using Vehicular Communications.
IEEE J. Sel. Areas Commun., 2013

A lane-level dynamic traffic control system for driving efficiency optimization based on vehicular networks.
Proceedings of the 2013 IEEE International Conference on Pervasive Computing and Communications Workshops, 2013

2012
A dynamic password-based user authentication scheme for hierarchical wireless sensor networks.
J. Netw. Comput. Appl., 2012

2011
Eco-Sign: a load-based traffic light control system for environmental protection with vehicular communications.
Proceedings of the ACM SIGCOMM 2011 Conference on Applications, 2011

On noise-enhanced distributed inference in the presence of Byzantines.
Proceedings of the 49th Annual Allerton Conference on Communication, 2011


  Loading...