Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbo...
BDDs and their algorithms implement a decision procedure for Quanti ed Propositional Logic. BDDs are a kind of acyclic automata. Unrestricted automata (recognizing unbounded string...
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
This paper addresses the problem of efficiently solving large-scale energy minimization problems encountered in computer vision. We propose an energy-aware method for merging ran...
Taesup Kim, Sebastian Nowozin, Pushmeet Kohli, Cha...