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JMLR
2002
115views more  JMLR 2002»
15 years 6 months ago
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Matthias Seeger
ML
2007
ACM
106views Machine Learning» more  ML 2007»
15 years 6 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
HIS
2008
15 years 8 months ago
Evolutionary Training Set Selection to Optimize C4.5 in Imbalanced Problems
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
Salvador García, Francisco Herrera
ACL
2006
15 years 8 months ago
A Hybrid Relational Approach for WSD - First Results
We present a novel hybrid approach for Word Sense Disambiguation (WSD) which makes use of a relational formalism to represent instances and background knowledge. It is built using...
Lucia Specia
ICAI
2004
15 years 7 months ago
Inductive System Health Monitoring
- The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficu...
David L. Iverson