73 citations · 218 across the 15 of their papers we have counts for
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math.OC2026
A stochastic subgradient method with optimal failure exponent
Bart P. G. van Parys
Fix a target accuracy , a gradient-noise level , and a horizon . We wish to design algorithms which minimize the probability of observing a suboptimality gap whi…
math.ST2026
Large and Moderate Deviations for Conservative Tail-Index Estimation
Martijn Gösgens, Bart P. G. van Parys, Bert Zwart
To design systems that are protected against events much rarer than the observational record, extreme-value methods are needed to extrapolate distribution tails. Tail-index estimat…
math.OC2026
Globalized Adversarial Regret Optimization: Robust Decisions with Uncalibrated Predictions
Jannis Kurtz, Bart P. G. van Parys
Optimization problems routinely depend on uncertain parameters that must be predicted before a decision is made. Classical robust and regret formulations are designed to handle err…