3 papers
math.OC2025
Distributional Adversarial Attacks and Training in Deep Hedging
Guangyi He, Tobias Sutter, Lukas Gonon
In this paper, we study the robustness of classical deep hedging strategies under distributional shifts by leveraging the concept of adversarial attacks. We first demonstrate that…
math.OC2025
Asymptotic Optimality in Data-Driven Decision Making
Radek Salač, Michael Kupper, Tobias Sutter
Given data generated by an observable stochastic process, we study how to construct statistically optimal decisions for general stochastic optimization problems. Our setting encomp…
cs.LG2025
Reliability-Adjusted Prioritized Experience Replay
Leonard S. Pleiss, Tobias Sutter, Maximilian Schiffer
Experience replay enables data-efficient learning from past experiences in online reinforcement learning agents. Traditionally, experiences were sampled uniformly from a replay buf…