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Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks

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Bibliographic Details
Published in:Journal of Machine Learning Research
Format: Online Article RSS Article
Published: 2026
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container_title Journal of Machine Learning Research
description
discipline_display e-Learning
discipline_facet e-Learning
format Online Article
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genre Journal Article
id rss_article:57199
institution FRELIP
journal_source_facet Journal of Machine Learning Research
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
e-Learning
General
e-Learning
sub_discipline_display General
sub_discipline_facet General
subject_display e-Learning
General
e-Learning
e-Learning
General
e-Learning
subject_facet e-Learning
General
e-Learning
title Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
title_auth Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
title_full Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
title_fullStr Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
title_full_unstemmed Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
title_short Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
title_sort approximation and optimization theory for linear continuous-time recurrent neural networks
topic e-Learning
General
e-Learning
url http://jmlr.org/papers/v23/21-0368.html