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Hierarchical multi-label classification using local neural networks
(ElsevierAcademic PressSan Diego, 2014-02)
Hierarchical multi-label classification is a complex classification task where the classes involved in the problem are hierarchically structured and each example may simultaneously belong to more than one class in each ...
Aprendizaje cooperativo de conceptos para sistemas Multi-Robot
(Instituto Nacional de Astrofísica, Óptica y Electrónica, 2009)
Incorporating label dependency into the binary relevance framework for multi-label classification
(PERGAMON-ELSEVIER SCIENCE LTDOXFORD, 2012)
In multi-label classification, examples can be associated with multiple labels simultaneously. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem ...
Dynamic task allocation with multiple demands and comunication failures for a multi-robot system
(Instituto Nacional de Astrofísica, Óptica y Electrónica, 2015)
Aprendizaje cooperativo de conceptos para sistemas Multi-Robot
(Instituto Nacional de Astrofísica, Óptica y Electrónica, 2009)
Learning to select the correct answer in multi-stream question answering
(Elsevier Ltd., 2011)
A new multi-label dataset for Web attacks CAPEC classification using machine learning techniques
Context: There are many datasets for training and evaluating models to detect web attacks, labeling each request as normal or attack. Web attack protection tools must provide additional information on the type of attack ...
On the implementation of a hardware architecture for an audio data hiding system
(Springer Science+Business Media, 2011)