Clustering validation is a long standing challenge in the clustering literature. While many validation measures have been developed for evaluating the performance of clustering al...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...
In this contribution, we explore the possibilities of learning in large-scale, multimodal processing systems operating under real-world conditions. Using an instance of a large-sca...
Mobile computing adds a mostly unexplored dimension to data mining: user's position is a relevant piece of information, and recommendation systems, selecting and ranking link...