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 131135 of 135 papers

TitleStatusHype
Towards Evaluating the Robustness of Neural Networks Learned by TransductionCode0
Fast Few-Shot Classification by Few-Iteration Meta-LearningCode0
FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry BenchmarkingCode0
Generating Accurate Pseudo-labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial ActivationsCode0
Distributed representations of graphs for drug pair scoringCode0
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