3 papers
cs.LG2026
Mirror Descent Beyond Euclidean Stability: An Exponential Separation in Initialization Sensitivity
Shira Vansover-Hager, Matan Schliserman, Ofir Schlisselberg +1
Mirror Descent (MD) extends Gradient Descent (GD) beyond Euclidean geometry and has recently reappeared as a lens for KL-regularized policy optimization in reinforcement learning a…
cs.LG2026
Flat Minima and Generalization: Insights from Stochastic Convex Optimization
Matan Schliserman, Shira Vansover-Hager, Tomer Koren
Understanding the generalization behavior of learning algorithms is a central goal of learning theory. A recently emerging explanation is that learning algorithms are successful in…
cs.LG2025
Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
Shira Vansover-Hager, Tomer Koren, Roi Livni
We study the out-of-sample performance of multi-pass stochastic gradient descent (SGD) in the fundamental stochastic convex optimization (SCO) model. While one-pass SGD is known to…