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ICML
2005
IEEE
15 years 10 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
ILP
1998
Springer
15 years 1 months ago
Strongly Typed Inductive Concept Learning
In this paper we argue that the use of a language with a type system, together with higher-order facilities and functions, provides a suitable basis for knowledge representation in...
Peter A. Flach, Christophe G. Giraud-Carrier, John...
ECML
2004
Springer
15 years 1 months ago
Efficient Hyperkernel Learning Using Second-Order Cone Programming
The kernel function plays a central role in kernel methods. Most existing methods can only adapt the kernel parameters or the kernel matrix based on empirical data. Recently, Ong e...
Ivor W. Tsang, James T. Kwok
CEC
2007
IEEE
15 years 1 months ago
Evolution of classification rules for comprehensible knowledge discovery
This article, which lies within the data mining framework, proposes a method to build classifiers based on the evolution of rules. The method, named REC (Rule Evolution for Classif...
Emiliano Carreno, Guillermo Leguizamón, Nea...
AIIA
2005
Springer
15 years 3 months ago
Handling Continuous-Valued Attributes in Incremental First-Order Rules Learning
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...