Sipta Seminar By Daniel Kuhn

ABSTRACT: Optimal Transport (OT) seeks the most efficient way to morph one probability distribution into another one, and ... Intersections between Control, Learning and Optimization 2020 "Wasserstein Distributionally Robust Optimization: Theory and ... ABSTRACT: The ability to generalise knowledge across diverse environments stands as a fundamental aspect of both biological ... ABSTRACT: Due to the growing relevance of machine learning for real-world applications, many of which are coming with safety ... ABSTRACT: Argumentation techniques have received significant attention in Artificial Intelligence, particularly since 1995, when ... ABSTRACT: Partially observable Markov decision processes (POMDPs) are the standard mathematical model for ...

ABSTRACT: The field of probabilistic circuits has seen a strong development during the last decade, in part by riding on the ... ABSTRACT: Bayesianism provides a powerful benchmark for treating uncertainty, on topics ranging from rational belief and ... ABSTRACT: Decision theory has seen many advancements since Savage (1972) from both the philosophical and IP communities. ABSTRACT: After a brief introduction to the concepts of classical decision theory relevant to us, the focus of the second part of the ... ABSTRACT: Imprecision in probability theory is often considered to be unfortunate, something to be tolerated, and then only if ... ABSTRACT: Imprecise probabilities (IP) capture structural uncertainty intrinsic to statistical models. They offer a richer vocabulary ...

ABSTRACT: The Poisson process is one of the more fundamental continuous-time uncertain processes. Besides its appearance ...