Originally, genetic algorithms were developed based on the binary representation of candidate solutions in which each conjectured solution is a fixed-length string of binary numb...
The problem of low-rank matrix factorization in the presence of missing data has seen significant attention in recent computer vision research. The approach that dominates the lit...
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Abstract. This paper presents an optimisation technique to select automatically a set of control parameters for a Markov Random Field applied to stereo matching. The method is base...
Riccardo Gherardi, Umberto Castellani, Andrea Fusi...
We propose and evaluate a new algorithm for checking the universality of nondeterministic finite automata. In contrast to the standard algorithm, which uses the subset construction...
Martin De Wulf, Laurent Doyen, Thomas A. Henzinger...