Title:
semi-supervized-learning
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Description: A PhD thesis on Semi-supervised learning with Graphs by Xiaojin Zhu. Focuses on creating graphs, based on a mixture of labeled and unlabeled data (as per the semi-supervised learning paradigm) and using processes on these graphs to propagate in rigorous way the labels from the labeled data to the unlabeled.
Applications in various areas in the Machine learning, such as text processing, image processing, pattern recognition, and others.
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semi supervized learning.pdf
