Adaptive multiple graph regularized semi-supervised extreme learning machine
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DOI: 10.1007/s00500-018-3109-x
Abstract: Semi-supervised extreme learning machine (SSELM) was proposed as an effective algorithm for machine learning and pattern recognition. However, the performance of SSELM heavily depends on whether the underlying geometrical structure of the data can be… read more here.
Keywords: machine; semi supervised; extreme learning; learning machine ... See more keywords
Safe Semi-Supervised Extreme Learning Machine for EEG Signal Classification
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DOI: 10.1109/access.2018.2868713
Abstract: One major challenge in the current brain–computer interface research is the accurate classification of time-varying electroencephalographic (EEG) signals. The labeled EEG samples are usually scarce, while the unlabeled samples are available in large quantities and… read more here.
Keywords: classification; semi supervised; extreme learning; unlabeled data ... See more keywords
Urban Traffic Congestion Evaluation Based on Kernel the Semi-Supervised Extreme Learning Machine
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DOI: 10.3390/sym9050070
Abstract: There is always an asymmetric phenomenon between traffic data quantity and unit information content. Labeled data is more effective but scarce, while unlabeled data is large but weaker in sample information. In an urban transportation… read more here.
Keywords: traffic; semi supervised; learning machine; extreme learning ... See more keywords