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» Evaluating learning algorithms and classifiers
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ECML
2007
Springer
14 years 3 months ago
Generalization-Based Similarity for Conceptual Clustering
The availability of techniques for comparing descriptions has many applications in Artificial Intelligence, ranging from description selection to flexible matching, from instance...
Stefano Ferilli, Teresa Maria Altomare Basile, Nic...
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
14 years 17 days ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski
ICML
2010
IEEE
13 years 10 months ago
Non-Local Contrastive Objectives
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...
David Vickrey, Cliff Chiung-Yu Lin, Daphne Koller
CSDA
2008
147views more  CSDA 2008»
13 years 9 months ago
Detection of unknown computer worms based on behavioral classification of the host
Machine learning techniques are widely used in many fields. One of the applications of machine learning in the field of the information security is classification of a computer be...
Robert Moskovitch, Yuval Elovici, Lior Rokach
GECCO
2008
Springer
177views Optimization» more  GECCO 2008»
13 years 10 months ago
Reduced computation for evolutionary optimization in noisy environment
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
Maumita Bhattacharya