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ECSQARU
2005
Springer
14 years 27 days ago
On the Use of Restrictions for Learning Bayesian Networks
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...
Luis M. de Campos, Javier Gomez Castellano

Source Code
1763views
15 years 4 months ago
dlib C++ Library
A library for developing portable applications that deal with networking, threads (message passing, futures, etc...), graphical interfaces, complex data structures, linear algebra,...
Davis E. King
ICDM
2002
IEEE
143views Data Mining» more  ICDM 2002»
14 years 10 days ago
A Hybrid Approach to Discover Bayesian Networks From Databases Using Evolutionary Programming
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
Man Leung Wong, Shing Yan Lee, Kwong-Sak Leung
CVPR
2012
IEEE
11 years 9 months ago
Weakly supervised structured output learning for semantic segmentation
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
GECCO
2004
Springer
14 years 23 days ago
Real-Coded Bayesian Optimization Algorithm: Bringing the Strength of BOA into the Continuous World
This paper describes a continuous estimation of distribution algorithm (EDA) to solve decomposable, real-valued optimization problems quickly, accurately, and reliably. This is the...
Chang Wook Ahn, Rudrapatna S. Ramakrishna, David E...