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APIN
1999
107views more  APIN 1999»
14 years 9 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
EC
2006
195views ECommerce» more  EC 2006»
14 years 9 months ago
Automated Global Structure Extraction for Effective Local Building Block Processing in XCS
Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are speci...
Martin V. Butz, Martin Pelikan, Xavier Llorà...
UAI
2003
14 years 11 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
ECCV
2010
Springer
15 years 2 months ago
Photo-consistent Planar Patches from Unstructured Cloud of Points
Abstract. Planar patches are a very compact and stable intermediate representation of 3D scenes, as they are a good starting point for a complete automatic reconstruction of surfac...
SIBGRAPI
2007
IEEE
15 years 4 months ago
Graph-based Object Tracking Using Structural Pattern Recognition
This paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), w...
Ana Beatriz V. Graciano, Roberto Marcondes Cesar J...