The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). ...
A. E. Eiben, Mark Horvath, Wojtek Kowalczyk, Marti...
Abstract. This paper proposes a novel approach named AGM to eciently mine the association rules among the frequently appearing substructures in a given graph data set. A graph tran...
We address the problem of non-rigid motion and correspondence estimation in 3D images in the absense of prior domain information. A generic framework is utilized in which a soluti...
We propose a method of deriving chronological order of events in natural language texts by constraining temporal boundaries associated to events and projecting them on a timeline....
Abstract. This paper proposes to use local search inside filtering algorithms of combinatorial structures for which achieving a desired level of consistency is too computationally ...
Philippe Galinier, Alain Hertz, Sandrine Paroz, Gi...