: High capacity associative neural networks can be built from networks of perceptrons, trained using simple perceptron training. Such networks perform much better than those traine...
We present DepQBF 0.1, a new search-based solver for quantified boolean formulae (QBF). It integrates compact dependency graphs to overcome the restrictions imposed by linear quan...
This work describes a framework for dealing with attention and categorization using a robot platform consisting of an articulated stereo-head with four degrees of freedom (pan, til...
We consider multi-armed bandit problems where the number of arms is larger than the possible number of experiments. We make a stochastic assumption on the mean-reward of a new sel...
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...