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» On Optimal Learning Algorithms for Multiplicity Automata
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ICML
2009
IEEE
14 years 8 months ago
More generality in efficient multiple kernel learning
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
Manik Varma, Bodla Rakesh Babu
GECCO
2000
Springer
121views Optimization» more  GECCO 2000»
13 years 11 months ago
Metaphor for learning: an evolutionary algorithm
The organizational algorithm is examined as a computational approach to representing interpersonal learning. The structure of the algorithm is introduced and described in context ...
Jody Lee Louse, Alexander Kain, James Hines
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
13 years 11 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
TNN
2010
159views Management» more  TNN 2010»
13 years 2 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
PAMI
2011
13 years 2 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang