Transductive Learning
28 papers with code • 0 benchmarks • 0 datasets
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.
Benchmarks
These leaderboards are used to track progress in Transductive Learning
Libraries
Use these libraries to find Transductive Learning models and implementationsMost implemented papers
Sparsity-aware neural user behavior modeling in online interaction platforms
With the rapid proliferation of such online services, learning data-driven user behavior models is indispensable to enable personalized user experiences.
View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes
kunzhan/VCHN
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IEEE Transactions on Cybernetics 2022
Performing transductive learning on graphs with very few labeled data, that is, two or three samples for each category, is challenging due to the lack of supervision.
TransBoost: Improving the Best ImageNet Performance using Deep Transduction
This paper deals with deep transductive learning, and proposes TransBoost as a procedure for fine-tuning any deep neural model to improve its performance on any (unlabeled) test set provided at training time.
Few-shot bioacoustic event detection at the DCASE 2022 challenge
c4dm/dcase-few-shot-bioacoustic
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This paper presents an overview of the second edition of the few-shot bioacoustic sound event detection task included in the DCASE 2022 challenge.
Distributed representations of graphs for drug pair scoring
paulmorio/drugpairscoringdr
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In this paper we study the practicality and usefulness of incorporating distributed representations of graphs into models within the context of drug pair scoring.
Fast Online Node Labeling for Very Large Graphs
This paper studies the online node classification problem under a transductive learning setting.
FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry Benchmarking
LorenzoBini4/FlowCyt-Classification-Benchmark
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This paper presents FlowCyt, the first comprehensive benchmark for multi-class single-cell classification in flow cytometry data.
Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection
c4dm/dcase-few-shot-bioacoustic
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A recent development in the field is the introduction of the task known as few-shot bioacoustic sound event detection, which aims to train a versatile animal sound detector using only a small set of audio samples.
