We consider probabilistic constrained linear programs with general distributions for the uncertain parameters. These problems generally involve non-convex feasible sets. We develo...
The paper introduces a framework for clustering data objects in a similarity-based context. The aim is to cluster objects into a given number of classes without imposing a hard pa...
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
We describe a new approach to model construction using transfer function diagrams that are consequently mapped into generalized loopy logic, a first-order, Turing-complete stochas...
Nikita A. Sakhanenko, Roshan Rammohan, George F. L...
Expert search, in which given a query a ranked list of experts instead of documents is returned, has been intensively studied recently due to its importance in facilitating the ne...