SOTAVerified

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 61–70 of 135 papers

TitleStatusHype
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives—0
On Label-Efficient Computer Vision: Building Fast and Effective Few-Shot Image ClassifiersCode0
Inductive Lottery Ticket Learning for Graph Neural Networks—0
Transductive Learning for Unsupervised Text Style TransferCode1
Semi-Supervised Domain Generalizable Person Re-IdentificationCode2
Joint Inductive and Transductive Learning for Video Object SegmentationCode1
Transductive image segmentation: Self-training and effect of uncertainty estimation—0
Towards Adversarial Robustness via Transductive Learning—0
GCNBoost: Artwork Classification by Label Propagation through a Knowledge Graph—0
Hypergraph Pre-training with Graph Neural Networks—0
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