Antesh Upadhyay

According to our database, Antesh Upadhyay authored at least 12 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Unified High-Probability Analysis of Stochastic Variance-Reduced Estimation.

Zhankun Luo, Antesh Upadhyay, Mehmet Berk Sahin, Sang Bin Moon, Anuran Makur, Abolfazl Hashemi

CoRR, May, 2026

Beyond Bounded Variance: Variance-Reduced Normalized Methods for Nonconvex Optimization under Blum-Gladyshev Noise.

Antesh Upadhyay, Arda Fazla, Abolfazl Hashemi

CoRR, May, 2026

Lower Bounds and Proximally Anchored SGD for Non-Convex Minimization Under Unbounded Variance.

Arda Fazla, Ege C. Kaya, Antesh Upadhyay, Abolfazl Hashemi

CoRR, April, 2026

First-Order Softmax Weighted Switching Gradient Method for Distributed Stochastic Minimax Optimization with Stochastic Constraints.

Zhankun Luo, Antesh Upadhyay, Sang Bin Moon, Abolfazl Hashemi

CoRR, March, 2026

FedSGM: A Unified Framework for Constraint Aware, Bidirectionally Compressed, Multi-Step Federated Optimization.

Antesh Upadhyay, Sang Bin Moon, Abolfazl Hashemi

CoRR, January, 2026

2024

Equitable Federated Learning with Activation Clustering.

Antesh Upadhyay, Abolfazl Hashemi

CoRR, 2024

FedNMUT - Federated Noisy Model Update Tracking Convergence Analysis.

Vishnu Pandi Chellapandi, Antesh Upadhyay, Abolfazl Hashemi, Stanislaw H. Zak

CoRR, 2024

Decentralized Federated Learning: Model Update Tracking Under Imperfect Information Sharing.

Vishnu Pandi Chellapandi, Antesh Upadhyay, Abolfazl Hashemi, Stanislaw H. Zak

Proceedings of the IEEE International Conference on Big Data, 2024

2023

On the Convergence of Decentralized Federated Learning Under Imperfect Information Sharing.

Vishnu Pandi Chellapandi, Antesh Upadhyay, Abolfazl Hashemi, Stanislaw H. Zak

IEEE Control. Syst. Lett., 2023

Improved Convergence Analysis and SNR Control Strategies for Federated Learning in the Presence of Noise.

Antesh Upadhyay, Abolfazl Hashemi

IEEE Access, 2023

Noisy Communication of Information in Federated Learning: An Improved Convergence Analysis.

Antesh Upadhyay, Abolfazl Hashemi

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

Predictive Estimation for Reinforcement Learning with Time-Varying Reward Functions.

Abolfazl Hashemi, Antesh Upadhyay

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023