We present a theoretical study on the discriminative clustering framework, recently proposed for simultaneous subspace selection via linear discriminant analysis (LDA) and cluster...
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
Recent research has made significant progress on the problem of bounding log partition functions for exponential family graphical models. Such bounds have associated dual paramete...
Many large -scale spatial data analysis problems involve an investigation of relationships in heterogeneous databases. In such situations, instead of making predictions uniformly a...
Aleksandar Lazarevic, Dragoljub Pokrajac, Zoran Ob...
We present a method for learning complex appearance mappings, such as occur with images of articulated objects. Traditional interpolation networks fail on this case since appearan...