We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
Finding linear correlations in dataset is an important data mining task, which can be widely applied in the real world. Existing correlation clustering methods combine clustering w...
Liang Tang, Changjie Tang, Lei Duan, Yexi Jiang, J...
When we construct a model of origami (a model of a folded sheet of paper) in a computer, it is usual to represent the model as a set of polygons having zero thickness. One of the t...
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...