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HIS
2007
13 years 9 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 7 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
KDD
2003
ACM
150views Data Mining» more  KDD 2003»
14 years 8 months ago
Learning relational probability trees
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...
GECCO
2006
Springer
153views Optimization» more  GECCO 2006»
13 years 11 months ago
Analysis of the difficulty of learning goal-scoring behaviour for robot soccer
Learning goal-scoring behaviour from scratch for simulated robot soccer is considered to be a very difficult problem, and is often achieved by endowing players with an innate set ...
Jeff Riley, Victor Ciesielski
STTT
2008
162views more  STTT 2008»
13 years 7 months ago
Coping with large design spaces: design problem solving in fluidic engineering
Abstract This paper is about tool support for knowledgeintensive engineering tasks. In particular, it introduces software technology to assist the design of complex technical syste...
Benno Stein