Showing math.OCShow all
2 papers · 1 filter
math.OC2025
Accelerated Gradient Methods with Biased Gradient Estimates: Risk Sensitivity, High-Probability Guarantees, and Large Deviation Bounds
Mert Gürbüzbalaban, Yasa Syed, Necdet Serhat Aybat
We study trade-offs between convergence rate and robustness to gradient errors in the context of first-order methods. Our focus is on generalized momentum methods (GMMs)--a broad c…
math.OC2024
High-probability complexity guarantees for nonconvex minimax problems
Yassine Laguel, Yasa Syed, Necdet Serhat Aybat +1
Stochastic smooth nonconvex minimax problems are prevalent in machine learning, e.g., GAN training, fair classification, and distributionally robust learning. Stochastic gradient d…