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cs.LG2026
Unified High-Probability Analysis of Stochastic Variance-Reduced Estimation
Zhankun Luo, Antesh Upadhyay, M. Berk Sahin +3
Stochastic estimators are fundamental to large-scale optimization, where population quantities must be inferred from noisy oracle observations. Although influential methods such as…
cs.LG2026
First-Order Softmax Weighted Switching Gradient Method for Distributed Stochastic Minimax Optimization with Stochastic Constraints
Zhankun Luo, Antesh Upadhyay, Sang Bin Moon +1
This paper addresses the distributed stochastic minimax optimization problem subject to stochastic constraints. We propose a novel first-order Softmax-Weighted Switching Gradient m…
cs.LG2026
Variance Reduction for Stochastic Switching in Functionally Constrained Federated Optimization
Antesh Upadhyay, Sang Bin Moon, Abolfazl Hashemi +1
Federated learning (FL) is increasingly used in safety-critical and fairness-sensitive applications, where learning objectives must be optimized subject to functional constraints.…