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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 101–110 of 135 papers

TitleStatusHype
Neural Transductive Learning and Beyond: Morphological Generation in the Minimal-Resource Setting—0
Deep Domain Adaptation under Deep Label Scarcity—0
Transductive Semi-Supervised Deep Learning using Min-Max Features—0
Improving the results of string kernels in sentiment analysis and Arabic dialect identification by adapting them to your test set—0
Inductive Two-Layer Modeling with Parametric Bregman Transfer—0
Identifying Key Sentences for Precision Oncology Using Semi-Supervised LearningCode0
Transductive Boltzmann Machines—0
Transductive Unbiased Embedding for Zero-Shot Learning—0
Bootstrap Domain-Specific Sentiment Classifiers from Unlabeled Corpora—0
Transductive Non-linear Learning for Chinese Hypernym Prediction—0
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