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 121130 of 135 papers

TitleStatusHype
Learning to learn via Self-CritiqueCode0
Predicting Strategic Behavior from Free TextCode0
Predictive Insights into LGBTQ+ Minority Stress: A Transductive Exploration of Social Media DiscourseCode0
Accurate and Scalable Graph Neural Networks via Message InvarianceCode0
Few-shot Novel Category DiscoveryCode0
Structure-Aware Consensus Network on Graphs with Few Labeled NodesCode0
Identifying Key Sentences for Precision Oncology Using Semi-Supervised LearningCode0
Unsupervised Tube Extraction Using Transductive Learning and Dense TrajectoriesCode0
Graph-based Interpolation of Feature Vectors for Accurate Few-Shot ClassificationCode0
UMFC: Unsupervised Multi-Domain Feature Calibration for Vision-Language ModelsCode0
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