Persistent Laplacian-enhanced algorithm for scarcely labeled data classification

The success of many machine learning (ML) methods depends crucially on having large amounts of labeled data. However, obtaining enough labeled data can be expensive, time-consuming, and subject to ethical constraints for many applications. One approach that has shown tremendous value in addressing t...

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Vydané v:	Machine learning Ročník 113; číslo 10; s. 7267 - 7292
Hlavní autori:	Bhusal, Gokul, Merkurjev, Ekaterina, Wei, Guo-Wei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.10.2024 Springer Nature B.V
Predmet:	Algorithms Artificial Intelligence Classification Computer Science Control Cost analysis Graph theory Machine Learning Mechatronics Natural language processing Natural Language Processing (NLP) Robotics Semi-supervised learning Simulation and Modeling Speech recognition Topology Scarcely labeled data Topology-based framework Persistent Laplacian Graph MBO technique
ISSN:	0885-6125, 1573-0565
On-line prístup:	Získať plný text
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