Abstract :
The following topics are dealt with: machine learning; data acquisition, cleansing and categorization; planning and reinforcement learning; supervised learning; multiparty, multimodal and multiobjective learning; feature selection; probabilistic and model based learning; similarity learning; pattern recognition; kernel learning; unsupervised learning; bioinformatics and computational biology; parallel computing; ensemble learning; Bayesian learning; incremental learning; biomedical literature analysis and text retrieval; dynamic learning; multimedia data; and cancer and radiation therapy.
Keywords :
Bayes methods; bioinformatics; cancer; data acquisition; data analysis; feature extraction; information retrieval; learning (artificial intelligence); multimedia computing; parallel processing; planning (artificial intelligence); probability; radiation therapy; text analysis; Bayesian learning; bioinformatics; biomedical literature analysis; cancer; computational biology; data acquisition; data categorization; data cleansing; dynamic learning; ensemble learning; feature selection; incremental learning; kernel learning; machine learning; model based learning; multimedia data; multimodal learning; multiobjective learning; multiparty learning; parallel computing; pattern recognition; planning; probabilistic learning; radiation therapy; reinforcement learning; similarity learning; text retrieval; unsupervised learning;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-9211-4
DOI :
10.1109/ICMLA.2010.172
