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IJAR
2007
130views more  IJAR 2007»
15 years 6 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
15 years 11 months ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...
ISNN
2007
Springer
16 years 26 days ago
Extensions of Manifold Learning Algorithms in Kernel Feature Space
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...
Yaoliang Yu, Peng Guan, Liming Zhang
CORR
2010
Springer
88views Education» more  CORR 2010»
15 years 6 months ago
A fuzzified BRAIN algorithm for learning DNF from incomplete data
Aim of this paper is to address the problem of learning Boolean functions from training data with missing values. We present an extension of the BRAIN algorithm, called U-BRAIN (U...
Salvatore Rampone, Ciro Russo
NIPS
2004
15 years 8 months ago
New Criteria and a New Algorithm for Learning in Multi-Agent Systems
We propose a new set of criteria for learning algorithms in multi-agent systems, one that is more stringent and (we argue) better justified than previous proposed criteria. Our cr...
Rob Powers, Yoav Shoham