In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
This paper describes how to automatically extract the presence and location of geometrical irregularities on a surface of revolution. To this end a partial 3D scan of the workpiec...
Kasper Claes, Thomas P. Koninckx, Herman Bruyninck...
This paper presents a new dependence language modeling approach to information retrieval. The approach extends the basic language modeling approach based on unigram by relaxing th...
Jianfeng Gao, Jian-Yun Nie, Guangyuan Wu, Guihong ...
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
Mark W. Schmidt, Alexandru Niculescu-Mizil, Kevin ...