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AI
2001
Springer
15 years 4 months ago
Learning Bayesian Belief Network Classifiers: Algorithms and System
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Jie Cheng, Russell Greiner
IJON
2010
120views more  IJON 2010»
14 years 10 months ago
Semi-supervised learning with varifold Laplacians
This paper presents varifold learning, a learning framework based on the mathematical concept of varifolds. Different from manifold based methods, our varifold learning framework ...
Lei Ding, Peibiao Zhao
COLING
2010
14 years 6 months ago
Generative Alignment and Semantic Parsing for Learning from Ambiguous Supervision
We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
Joohyun Kim, Raymond J. Mooney
ICARIS
2009
Springer
15 years 6 months ago
On AIRS and Clonal Selection for Machine Learning
AIRS is an immune-inspired supervised learning algorithm that has been shown to perform competitively on some common datasets. Previous analysis of the algorithm consists almost ex...
Chris McEwan, Emma Hart
CEC
2005
IEEE
15 years 5 months ago
Revisiting genetic selection in the XCS learning classifier system
The XCS Learning Classifier System has traditionally used roulette wheel selection within its genetic algorithm component. Recently, tournament selection has been suggested as prov...
Faten Kharbat, Larry Bull, Mohammed Odeh