This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
The purpose of this paper is to generalize a result by Donoho, Huo, Elad and Bruckstein on sparse representations of signals/images in a union of two orthonormal bases. We conside...
We propose an adaptive decomposition algorithm to compute separation distances between arbitrarily shaped objects. Using the Gilbert-JohnsonKeerthi algorithm (GJK), we search for ...
In this paper, we propose the application of standard decomposition approaches to find local correlations in multimodal data. In a test scenario, we apply these methods to correla...
Daniel Dornbusch, Robert Haschke, Stefan Menzel, H...
—This paper presents an operational rate-distortion (ORD) optimal approach for skeleton-based boundary encoding. The boundary information is first decomposed into skeleton and di...
Haohong Wang, Guido M. Schuster, Aggelos K. Katsag...