Abstract. A new dictionary learning method for exact sparse representation is presented in this paper. As the dictionary learning methods often iteratively update the sparse coeffi...
This paper introduces a compact representation which helps to avoid the exponential blow-up in space of the Least Common Subsumer (lcs) of two ALEconcept descriptions. Based on th...
Chan Le Duc, Nhan Le Thanh, Marie-Christine Rousse...
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
Fundamental to data cleaning is the need to account for multiple data representations. We propose a formal framework that can be used to reason about and manipulate data represent...
We address the problem of image search on a very large scale, where three constraints have to be considered jointly: the accuracy of the search, its efficiency, and the memory usag...