AAAI
2010
13 years 9 months ago
2010
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
KI
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Markov logic, as a highly expressive representation formalism that essentially combines the semantics of probabilistic graphical models with the full power of first-orde...
ECML
2007
Springer
14 years 1 months ago
2007
Springer
Imitation-based learning is a general mechanism for rapid acquisition of new behaviors in autonomous agents and robots. In this paper, we propose a new approach to learning by imit...
P2P
2007
IEEE
14 years 1 months ago
2007
IEEE
This paper proposes to utilize algorithms from the probabilistic graphical models domain for Peer-to-Peer rating of data items and for computing “social influence” of nodes i...
IEEEARES
2008
IEEE
14 years 1 months ago
2008
IEEE
Reliability analysis has become an integral part of system design and operating. This is especially true for systems performing critical tasks such as mass transportation systems....
PKDD
2009
Springer
14 years 1 months ago
2009
Springer
Probabilistic logics have attracted a great deal of attention during the past few years. While logical languages have taken a central position in research on knowledge representati...
ICDAR
2009
IEEE
14 years 2 months ago
2009
IEEE
Hidden Markov Models (HMM) are probabilistic graphical models for interdependent classification. In this paper we experiment with different ways of combining the components of an ...
RECOMB
2007
Springer
14 years 7 months ago
2007
Springer
We present a technique for approximating the free energy of protein structures using Generalized Belief Propagation (GBP). The accuracy and utility of these estimates are then demo...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...