We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
We present a novel technique that speeds up state-space exploration (SSE) for evolving programs with dynamically allocated data. SSE is the essence of explicit-state model checkin...
Steven Lauterburg, Ahmed Sobeih, Darko Marinov, Ma...
The research objective of this work is to develop a general framework that incorporates collaborative social tagging with a novel ontology scheme conveying multiple perspectives. ...