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» Approximate dynamic programming: Lessons from the field
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NIPS
2007
13 years 9 months ago
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
MP
1998
109views more  MP 1998»
13 years 7 months ago
Rounding algorithms for covering problems
In the last 25 years approximation algorithms for discrete optimization problems have been in the center of research in the fields of mathematical programming and computer science...
Dimitris Bertsimas, Rakesh V. Vohra
SIAMIS
2010
378views more  SIAMIS 2010»
13 years 2 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
JMLR
2006
125views more  JMLR 2006»
13 years 7 months ago
Linear Programming Relaxations and Belief Propagation - An Empirical Study
The problem of finding the most probable (MAP) configuration in graphical models comes up in a wide range of applications. In a general graphical model this problem is NP hard, bu...
Chen Yanover, Talya Meltzer, Yair Weiss
SPIN
2000
Springer
13 years 11 months ago
Communication Topology Analysis for Concurrent Programs
Abstract. In this article, we address the problem of statically determining an approximation of the communication topology of concurrent programs. These programs may contain dynami...
Matthieu Martel, Marc Gengler