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Transfer learning

Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. For example, for image classification, knowledge gained while learning to recognize cars could be applied when trying to recognize trucks. This topic is related to the psychological literature…

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Overview

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  • ISBN ISBN (identifier)

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Map overview Semantic statistics

Transfer learning

Nodes29
Edges28
Triples20
Avg. degree1.93
Density0.068966
Components1

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Transfer learning

Top relations

has application · 11
Transfer learning → Algorithms, Bayesian, EEG, EMG, In, It, Markov, Moreover, That, The, Transfer
related to history · 6
Transfer learning → Bozinovski, DBT, Fulgosi, In, Lorien Pratt, The
related to Definition · 3
Transfer learning → Given, The, This

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Important terminology

learning transfer domain displaystyle related mathcal task machine knowledge learned improve training paper given function tl performance classification applied topic

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Transfer learninghas applicationAlgorithms0.60section
Transfer learninghas applicationMarkov0.60section
Transfer learninghas applicationBayesian0.60section
Transfer learninghas applicationTransfer0.60section
Transfer learninghas applicationIn0.60section
Transfer learninghas applicationEMG0.60section
Transfer learninghas applicationEEG0.60section
Transfer learninghas applicationIt0.60section
Transfer learninghas applicationThe0.60section
Transfer learninghas applicationThat0.60section
Transfer learninghas applicationMoreover0.60section
Transfer learningrelated to DefinitionThe0.60section

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    Min side: 3
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