Classification and semi-supervised learning;.- Clustering and kernel.-Application to recognition.- Sampling and big data.- Application to detection.- Decision tree learning; learning and adaptation.- Similarity and decision making.- Learning with uncertainty.- Improved learning algorithms and applications.
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