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Poster Abstract: A Maximal Correlation Embedding Method for Multilabel Human Context Recognition

Real-time human context recognition is one of the most exciting emerging technologies in sensing nowadays. Compared with most recognition problems in machine learning, the challenge lies in the complexity and incompleteness of labels, in other words, each sample can have several label concepts simultaneously but some of them could be missing. This poster proposes an effective approach for multilabel human context recognition with signals from sensors embedded in the wearable devices. The proposed algorithm demonstrates to be very robust to incomplete labels.