Do you know the difference between an optimist and a pessimist? The former believes we
live in the best possible world, and the latter is afraid that the former might be right.… In that …

We perform a comprehensive study on the performance of derivative free optimization (DFO)
algorithms for the generation of targeted black-box adversarial attacks on Deep Neural …

We introduce a general framework for large-scale model-based derivative-free optimization
based on iterative minimization within random subspaces. We present a probabilistic worst …

Black-box optimization plays a pivotal role in addressing complex real-world problems
where the underlying mathematical model is unknown or expensive to evaluate. In this …

Derivative-free-or zeroth-order-optimization (DFO) has gained recent attention for its ability
to solve problems in a variety of application areas, including machine learning, particularly …

Abstract Parallel-in-time (PinT) methods were developed to accelerate time-domain solution
of evolutionary problems using modern parallel computer architectures. In this paper we …

Though ubiquitous in applications, global optimisation problems are generally the most
computationally intense due to their solution time growing exponentially with linear increase …

Diese Arbeit beschäftigt sich mit der Simulation und Formoptimierung von
elektromechanischen Energiewandlern unter Unsicherheit. Genauer wird eine …

Over the last decade, the academic and industrial communities have become increasingly
involved in the field of Deep Learning, leading these algorithms to become the drivers of the …

Black-box optimization plays a pivotal role in addressing complex real-world problems
where the underlying mathematical model is unknown or expensive to evaluate. In this …