How well can the maximum size of an independent set, or the minimum size of a dominating set of a graph in which all degrees are at most d be approximated by a randomized constant...
Most machine learning algorithms share the following drawback: they only output bare predictions but not the con dence in those predictions. In the 1960s algorithmic information t...
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
Real-world distributed systems and networks are often unreliable and subject to random failures of its components. Such a stochastic behavior affects adversely the complexity of o...
A biologically inspired cognitive model is presented for human decision making and applied to the simulation of the web user. The model is based on the Neurophysiology description ...