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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 121–130 of 135 papers

Title	Date	Tasks	Status
DC Proximal Newton for Non-Convex Optimization Problems	Jul 2, 2015	Transductive Learning	—Unverified
Permutational Rademacher Complexity: a New Complexity Measure for Transductive Learning	May 12, 2015	Learning TheoryTransductive Learning	—Unverified
Transductive Multi-class and Multi-label Zero-shot Learning	Mar 26, 2015	Multi-label zero-shot learningTransductive Learning	—Unverified
Transductive Multi-label Zero-shot Learning	Mar 26, 2015	Multi-label zero-shot learningregression	—Unverified
Deep Transductive Semi-supervised Maximum Margin Clustering	Jan 26, 2015	ClusteringTransductive Learning	—Unverified
Localized Complexities for Transductive Learning	Nov 26, 2014	Learning TheoryTransductive Learning	—Unverified
Transductive Learning for Multi-Task Copula Processes	Jun 2, 2014	Gaussian ProcessesMulti-Task Learning	—Unverified
Machine Translation Model based on Non-parallel Corpus and Semi-supervised Transductive Learning	May 22, 2014	Machine TranslationTransductive Learning	—Unverified
Transductive Learning with Multi-class Volume Approximation	Feb 3, 2014	Transductive Learning	—Unverified
Transductive Rademacher Complexity and its Applications	Jan 15, 2014	Transductive Learning	—Unverified

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