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Transductive Learning

In this setting, both a labeled training sample and an (unlabeled) test sample are provided at training time. The goal is to predict only the labels of the given test instances as accurately as possible.

Papers

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Showing 126–135 of 135 papers

TitleStatusHype
Localized Complexities for Transductive Learning—0
Transductive Learning for Multi-Task Copula Processes—0
Machine Translation Model based on Non-parallel Corpus and Semi-supervised Transductive Learning—0
Transductive Learning with Multi-class Volume Approximation—0
Transductive Rademacher Complexity and its Applications—0
Selective Transfer Machine for Personalized Facial Action Unit Detection—0
Computationally Efficient Regression on a Dependency Graph for Human Pose Estimation—0
Document and Corpus Level Inference For Unsupervised and Transductive Learning of Information Structure of Scientific Documents—0
Relax and Randomize : From Value to Algorithms—0
Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification—0
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