It is a difficult task to design transfer functions for noisy data. In traditional transfer-function spaces, data values of different materials overlap. In this paper we introduce...
Martin Haidacher, Daniel Patel, Stefan Bruckner, A...
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
In this paper, we propose a new technique to perform figure-ground segmentation in image sequences of moving objects under varying illumination conditions. Unlike most of the alg...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
In this paper, we describe development of a mobile robot which does unsupervised learning for recognizing an environment from action sequences. We call this novel recognition appr...
Distributed coding at the hidden layer of a multi-layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically req...
Gail A. Carpenter, Boriana L. Milenova, Benjamin W...