iTimes: Investigating Semisupervised Time Series Classification via Irregular Time Sampling
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DOI: 10.1109/tii.2022.3199374
Abstract: Semi-supervised learning (SSL) provides a powerful paradigm to mitigate the reliance on large labeled data by leveraging unlabeled data during model training. However, for time series data, few SSL models focus on the underlying temporal… read more here.
Keywords: time; time series; semisupervised time; irregular time ... See more keywords