2 papers
cs.LG2026
PurSAMERE: Reliable Adversarial Purification via Sharpness-Aware Minimization of Expected Reconstruction Error
Vinh Hoang, Sebastian Krumscheid, Holger Rauhut +1
We propose a novel deterministic purification method to improve adversarial robustness by mapping a potentially adversarial sample toward a nearby sample that lies close to a mode…
math.OC2025
Efficient Stochastic BFGS methods Inspired by Bayesian Principles
André Carlon, Luis Espath, Raúl Tempone
Quasi-Newton methods are ubiquitous in deterministic local search due to their efficiency and low computational cost. This class of methods uses the history of gradient evaluations…