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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 31–40 of 135 papers

TitleStatusHype
Transductive Learning for Near-Duplicate Image Detection in Scanned Photo Collections—0
VLSI Hypergraph Partitioning with Deep Learning—0
Structure-Aware Consensus Network on Graphs with Few Labeled NodesCode0
Anomaly Detection of Tabular Data Using LLMs—0
Bayesian Circular Regression with von Mises Quasi-Processes—0
The Benefits and Risks of Transductive Approaches for AI Fairness—0
Graph Transductive Defense: a Two-Stage Defense for Graph Membership Inference Attacks—0
Is Transductive Learning Equivalent to PAC Learning?—0
FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry BenchmarkingCode0
Hyperdimensional Representation Learning for Node Classification and Link Prediction—0
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