In a preliminary part of this paper, we analyze the necessity of randomness in evolution strategies. We conclude to the necessity of ”continuous”-randomness, but with a much m...
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
Evaluation of incomplete algorithms that solve SAT requires to generate hard satisfiable instances. For that purpose, the kSAT uniform random generation is not usable. The other g...
In this paper we propose a novel approach to content-based image retrieval with relevance feedback, which is based on the random walker algorithm introduced in the context of inte...