Erind Bedalli

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Semi-supervised learning is an eminent domain of machine learning focusing on real-life problems where the labeled data instances are scarce. This paper innovatively extends existing factorization models into a supervised nonlinear factorization. The current state of the art methods for semi-supervised regression are based on supervised manifold(More)
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