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COLT
1994
Springer
15 years 4 months ago
Bayesian Inductive Logic Programming
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
Stephen Muggleton
81
Voted
IJCNN
2006
IEEE
15 years 6 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang
PPSN
2004
Springer
15 years 6 months ago
Learning Probabilistic Tree Grammars for Genetic Programming
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Peter A. N. Bosman, Edwin D. de Jong
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
15 years 5 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
105
Voted
CMSB
2004
Springer
15 years 6 months ago
Modelling Metabolic Pathways Using Stochastic Logic Programs-Based Ensemble Methods
In this paper we present a methodology to estimate rates of enzymatic reactions in metabolic pathways. Our methodology is based on applying stochastic logic learning in ensemble le...
Huma Lodhi, Stephen Muggleton