47 citations · 59 across the 6 of their papers we have counts for
6 papers
Confidence Estimation via Sequential Likelihood Mixing
Johannes Kirschner, Andreas Krause, Michele Meziu +1
We present a universal framework for constructing confidence sets based on sequential likelihood mixing. Building upon classical results from sequential analysis, we provide a unif…
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
Melis Ilayda Bal, Pier Giuseppe Sessa, Mojmir Mutny +1
Bayesian optimization (BO) is a powerful framework to optimize black-box expensive-to-evaluate functions via sequential interactions. In several important problems (e.g. drug disco…
Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory
Lenart Treven, Sebastian Curi, Mojmir Mutny +1
The principal task to control dynamical systems is to ensure their stability. When the system is unknown, robust approaches are promising since they aim to stabilize a large set of…
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
Johannes Kirschner, Mojmír Mutný, Nicole Hiller +2
Bayesian optimization is known to be difficult to scale to high dimensions, because the acquisition step requires solving a non-convex optimization problem in the same search space…
Stochastic Second-Order Optimization via von Neumann Series
Mojmir Mutny
A stochastic iterative algorithm approximating second-order information using von Neumann series is discussed. We present convergence guarantees for strongly-convex and smooth func…
Learning the Correction for Multi-Path Deviations in Time-of-Flight Cameras
Mojmir Mutny, Rahul Nair, Jens-Malte Gottfried
The Multipath effect in Time-of-Flight(ToF) cameras still remains to be a challenging problem that hinders further processing of 3D data information. Based on the evidence from pre…