In this paper we introduce a novel method to address minimization of static and dynamic MRFs. Our approach is based on principles from linear programming and, in particular, on pr...
We present a simple and scalable algorithm for maximum-margin estimation of structured output models, including an important class of Markov networks and combinatorial models. We ...
Benjamin Taskar, Simon Lacoste-Julien, Michael I. ...
— This paper introduces a novel algorithm for haptic interaction with an adaptive simulation of articulated-body dynamics. Our algorithm has a multi-threaded structure, which all...
We present a framework for decision making with the possibility to express circumstance-dependent preferences among different alternatives for a decision. This new formalism, Order...
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...