2 papers
cs.LG2026
A projection-based framework for gradient-free and parallel learning
Andreas Bergmeister, Manish Krishan Lal, Stefanie Jegelka +1
We present a feasibility-seeking approach to neural network training. This mathematical optimization framework is distinct from conventional gradient-based loss minimization and us…
cs.LG2025
Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond
Tasuku Soma, Khashayar Gatmiry, Sharut Gupta +1
Distributionally robust optimization (DRO) can improve the robustness and fairness of learning methods. In this paper, we devise stochastic algorithms for a class of DRO problems i…