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HIS
2007
13 years 11 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
CE
2006
161views more  CE 2006»
13 years 9 months ago
Applying an authentic, dynamic learning environment in real world business
This paper describes a dynamic computer-based business learning environment and the results from applying it in a real-world business organization. We argue for using learning too...
Timo Lainema, Sami Nurmi
GECCO
2004
Springer
100views Optimization» more  GECCO 2004»
14 years 3 months ago
Transfer of Neuroevolved Controllers in Unstable Domains
In recent years, the evolution of artificial neural networks or neuroevolution has brought promising results in solving difficult reinforcement learning problems. But, like standa...
Faustino J. Gomez, Risto Miikkulainen
FSKD
2006
Springer
147views Fuzzy Logic» more  FSKD 2006»
14 years 1 months ago
Adaptive Nearest Neighbor Classifier Based on Supervised Ellipsoid Clustering
Nearest neighbor classifier is a widely-used effective method for multi-class problems. However, it suffers from the problem of the curse of dimensionality in high dimensional spac...
Guo-Jun Zhang, Ji-Xiang Du, De-Shuang Huang, Tat-M...
SIGPRO
2011
209views Hardware» more  SIGPRO 2011»
13 years 4 months ago
Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms
In this paper, we survey and compare different algorithms that, given an overcomplete dictionary of elementary functions, solve the problem of simultaneous sparse signal approxim...
A. Rakotomamonjy