T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data

Bibliografski detalji

Izdano u:	arXiv.org (Dec 19, 2024), p. n/a
Glavni autor:	Thimonier, Hugo
Daljnji autori:	José Lucas De Melo Costa, Popineau, Fabrice, Rimmel, Arpad, Doan, Bich-Liên
Izdano:	Cornell University Library, arXiv.org
Teme:	Structured data Regularization methods Regularization Data augmentation Self-supervised learning Tables (data) Machine learning Decision trees Representations
Online pristup:	Citation/Abstract Full text outside of ProQuest
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