Abstract. In this paper we elaborate on a kernel extension to tensorbased data analysis. The proposed ideas find applications in supervised learning problems where input data have ...
Marco Signoretto, Lieven De Lathauwer, Johan A. K....
Abstract. In this paper, we propose a novel approach for action classification in soccer videos using a recurrent neural network scheme. Thereby, we extract from each video action ...
Moez Baccouche, Franck Mamalet, Christian Wolf, Ch...
Abstract. The Self-Organising Map (SOM) is a well-known neuralnetwork model that has successfully been used as a data analysis tool in many different domains. The SOM provides a to...
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
We present a biologically inspired neural network model of visual orienting (using saccadic eye movements) in which targets are preferentially selected according to their reward va...
We shed light on the key ingredients of reservoir computing and analyze the contribution of the network dynamics to the spatial encoding of inputs. Therefore, we introduce attracto...
We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...
Christian Vollmer, Erik Schaffernicht, Horst-Micha...
One way to handle the perception of images that change in position (or size, orientation or deformation) is to invoke rapidly changing fiber projections to project images into a fi...
Junmei Zhu, Urs Bergmann, Christoph von der Malsbu...