In this work we present a unified view on Markov random fields and recently proposed continuous tight convex relaxations for multi-label assignment in the image plane. These rel...
Abstract. In this theoretical paper we consider the problem of accurately triangulating a scene plane. Rather than first triangulating a set of points and then fitting a plane to...
In this work we present the Partner Units Problem as a novel challenge for optimization methods. It captures a certain type of configuration problem that frequently occurs in indu...
Markus Aschinger, Conrad Drescher, Gerhard Friedri...
Transfer learning aims to solve new learning problems by extracting and making use of the common knowledge found in related domains. A key element of transfer learning is to ident...
Qiang Yang, Vincent Wenchen Zheng, Bin Li, Hankz H...
Some real-world problems are partially decomposable, in that they can be decomposed into a set of coupled subproblems, that are each relatively easy to solve. However, when these ...
This work is a suitability study of the different optimization methods for automated parameter estimation (fitting) in the context of neuronal signaling networks. The Gepasi simul...
A population based real-time optimization method for tuning dynamic position control parameters of robot manipulators has been proposed. Conventionally, the positional control is a...
An efficient “Simulation Optimization” technique is developed to solve system design problems which can not be expressed in explicit analytical or mathematical models. In part...
Developing scalable algorithms for solving partially observable Markov decision processes (POMDPs) is an important challenge. One promising approach is based on representing POMDP...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...