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

Showing 1120 of 135 papers

TitleStatusHype
View-Consistent Heterogeneous Network on Graphs With Few Labeled NodesCode1
Sparsity-aware neural user behavior modeling in online interaction platformsCode1
HGATE: Heterogeneous Graph Attention Auto-EncodersCode1
Transductive Learning for Unsupervised Text Style TransferCode1
Joint Inductive and Transductive Learning for Video Object SegmentationCode1
BertGCN: Transductive Text Classification by Combining GCN and BERTCode1
DINE: Domain Adaptation from Single and Multiple Black-box PredictorsCode1
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural NetworksCode1
Embedding Propagation: Smoother Manifold for Few-Shot ClassificationCode1
Geom-GCN: Geometric Graph Convolutional NetworksCode1
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