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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 26–50 of 135 papers

TitleStatusHype
Anomaly Detection of Tabular Data Using LLMs—0
Active Few-Shot Fine-Tuning—0
Inductive Graph Neural Networks for Moving Object Segmentation—0
Improving the results of string kernels in sentiment analysis and Arabic dialect identification by adapting them to your test set—0
A Simple Hypergraph Kernel Convolution based on Discounted Markov Diffusion Process—0
Deep Transductive Semi-supervised Maximum Margin Clustering—0
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples—0
Transductive Learning Is Compact—0
Deep Domain Adaptation under Deep Label Scarcity—0
HONEM: Learning Embedding for Higher Order Networks—0
DC Proximal Newton for Non-Convex Optimization Problems—0
Data Selection with Feature Decay Algorithms Using an Approximated Target Side—0
Automatic Organization of Neural Modules for Enhanced Collaboration in Neural Networks—0
An Iterative Co-Training Transductive Framework for Zero Shot Learning—0
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications—0
Generate, Transduct, Adapt: Iterative Transduction with VLMs—0
Graph Transductive Defense: a Two-Stage Defense for Graph Membership Inference Attacks—0
GCNBoost: Artwork Classification by Label Propagation through a Knowledge Graph—0
Cross-Graph Learning of Multi-Relational Associations—0
f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning—0
Hypergraph Pre-training with Graph Neural Networks—0
From Emotions to Action Units With Hidden and Semi-Hidden-Task Learning—0
Incremental Transductive Learning Approaches to Schistosomiasis Vector Classification—0
Cross-domain aspect extraction for sentiment analysis: a transductive learning approach—0
A transductive few-shot learning approach for classification of digital histopathological slides from liver cancer—0
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