We study best approximation problems with nonlinear constraints in Hilbert spaces. The strong "conical hull intersection property" (CHIP) and the "basic constraint q...
A new framework is presented that uses tools from duality theory of linear programming to derive graph-cut based combinatorial algorithms for approximating NP-hard classification ...
This paper presents a method to speed up support vector classification, especially important when data is highdimensional. Unlike previous approaches which focus on less support v...
In content based image retrieval, the success of any distance-based indexing scheme depends critically on the quality of the chosen distance metric. We propose in this paper a ker...
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...