It is possible to model avatars that learn to simulate object manipulations and other complex actions. A number of applications may benefit from this technique including safety, e...
This paper investigates the problem ofautomatically learning declarative models of information sources available on the Internet. We report on ILA, a domain-independent program th...
We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...
Independent component analysis (ICA) is a powerful method to decouple signals. Most of the algorithms performing ICA do not consider the temporal correlations of the signal, but o...
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...