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Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective

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Bibliographic Details
Published in:Journal of Machine Learning Research (JMLR)
Format: Online Article RSS Article
Published: 2026
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container_title Journal of Machine Learning Research (JMLR)
description
discipline_display Computer Sciience
discipline_facet Computer Sciience
format Online Article
RSS Article
genre Journal Article
id rss_article:77715
institution FRELIP
journal_source_facet Journal of Machine Learning Research (JMLR)
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective
Computer Sciience
General
Computer Sciience
sub_discipline_display General
sub_discipline_facet General
subject_display Computer Sciience
General
Computer Sciience
Computer Sciience
General
Computer Sciience
subject_facet Computer Sciience
General
Computer Sciience
title Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective
title_auth Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective
title_full Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective
title_fullStr Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective
title_full_unstemmed Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective
title_short Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective
title_sort transformers can overcome the curse of dimensionality: a theoretical study from an approximation perspective
topic Computer Sciience
General
Computer Sciience
url http://jmlr.org/papers/v27/25-1214.html