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GECCO
2004
Springer
150views Optimization» more  GECCO 2004»
14 years 2 months ago
Parameter Adaptation within Co-adaptive Learning Classifier Systems
The authors propose a co-adaptive approach to controlling parameters for coevolution-based learning classifier systems. By taking advantage of the on-line incremental learning capa...
Chung-Yuan Huang, Chuen-Tsai Sun
IJCAI
1989
13 years 10 months ago
Noise-Tolerant Instance-Based Learning Algorithms
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
David W. Aha, Dennis F. Kibler
KDD
1999
ACM
199views Data Mining» more  KDD 1999»
14 years 1 months ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang
UAI
2003
13 years 10 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...
AAAI
1996
13 years 10 months ago
Constructive Neural Network Learning Algorithms
Constructive learning algorithms offer an attractive approach for the incremental construction of near-minimal neural-network architectures for pattern classification. They help ov...
Rajesh Parekh, Jihoon Yang, Vasant Honavar