Labelled Markov processes (LMPs) are automata whose transitions are given by probability distributions. In this paper we present a ‘universal’ LMP as the spectrum of a commutat...
Abstract. We derive a continuous probability distribution which generates neighbours of a point in an interval in a similar way to the bitwise mutation of a Gray code binary string...
Abstract. In constraint satisfaction, a general rule is to tackle the hardest part of a search problem first. In this paper, we introduce a parameter (τ) that measures the constr...
Abstract. Classical learning algorithms from the fields of artificial neural networks and machine learning, typically, do not take any costs into account or allow only costs depe...
Abstract. We compare two successful discriminative classification algorithms on three databases from the UCI and STATLOG repositories. The two approaches are the log-linear model ...
Daniel Keysers, Roberto Paredes, Enrique Vidal, He...