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The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised… Expand Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans… Expand It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from… Expand In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in… Expand A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical… Expand This chapter contains sections titled: Supervised, Unsupervised, and Semi-Supervised Learning, When Can Semi-Supervised Learning… Expand Social network analysis has attracted much attention in recent years. Link prediction is a key research directions within this… Expand We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this… Expand An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data… Expand A supervised learning algorithm (Scaled Conjugate Gradient, SCG) is introduced. The performance of SCG is benchmarked against… Expand