We propose a mid-level image segmentation framework that combines multiple figure-ground hypothesis (FG) constrained at different locations and scales, into interpretations that t...
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fiel...
Sebastian Nowozin, Carsten Rother, Shai Bagon, Ban...
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Abstract. We address the issue of efficiently automating assume-guarantee reasoning for simulation conformance between finite state systems and specifications. We focus on a non...
Sagar Chaki, Edmund M. Clarke, Nishant Sinha, Pras...
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...