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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 91–100 of 135 papers

TitleStatusHype
Transductive Learning for Zero-Shot Object Detection—0
Characterize and Transfer Attention in Graph Neural Networks—0
Generating Accurate Pseudo-labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial ActivationsCode0
HONEM: Learning Embedding for Higher Order Networks—0
Learning to learn via Self-CritiqueCode0
Label Propagation for Deep Semi-supervised LearningCode0
f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning—0
Data Selection with Feature Decay Algorithms Using an Approximated Target Side—0
Transductive Learning with String Kernels for Cross-Domain Text Classification—0
Cross-domain aspect extraction for sentiment analysis: a transductive learning approach—0
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