3 papers
cs.LG2026
Mitigating Spurious Correlations with Memorization-Guided Dataset De-Biasing
Arda Fazla, Abolfazl Hashemi
Real-world datasets often contain spurious correlations that are not causally related to the target label. When such correlations dominate the majority of training samples, models…
cs.LG2026
Beyond Bounded Variance: Variance-Reduced Normalized Methods for Nonconvex Optimization under Blum-Gladyshev Noise
Antesh Upadhyay, Arda Fazla, Abolfazl Hashemi
We study nonconvex stochastic optimization under the Blum-Gladyshev (-0) noise model, where the stochastic gradient variance grows quadratically with the distance from…
cs.LG2026
Lower Bounds and Proximally Anchored SGD for Non-Convex Minimization Under Unbounded Variance
Arda Fazla, Ege C. Kaya, Antesh Upadhyay +1
Analysis of Stochastic Gradient Descent (SGD) and its variants typically relies on the assumption of uniformly bounded variance, a condition that frequently fails in practical non-…