Federated Learning on Multilabel Evolving Data Streams
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DOI: 10.1109/jiot.2025.3592954
Abstract: Multilabel classification in distributed evolving data stream environment presents significant challenges, including addressing distributed concept drifts and label dependencies. In this study, we introduce two novel solutions employing federated learning (FL) problem transformation techniques to… read more here.
Keywords: learning multilabel; evolving data; multilabel; federated learning ... See more keywords
Ensemble Deep Learning for Multilabel Binary Classification of User-Generated Content
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DOI: 10.3390/a13040083
Abstract: Sentiment analysis usually refers to the analysis of human-generated content via a polarity filter. Affective computing deals with the exact emotions conveyed through information. Emotional information most frequently cannot be accurately described by a single… read more here.
Keywords: learning multilabel; ensemble deep; classification; deep learning ... See more keywords