{"id":7463,"date":"2025-10-09T07:02:26","date_gmt":"2025-10-09T07:02:26","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/10\/09\/2510-06372\/"},"modified":"2025-10-09T07:02:26","modified_gmt":"2025-10-09T07:02:26","slug":"2510-06372","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/10\/09\/2510-06372\/","title":{"rendered":"A General Constructive Upper Bound on Shallow Neural Nets Complexity"},"content":{"rendered":"<p>    A General Constructive Upper Bound on Shallow Neural Nets Complexity<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>arXiv:2510.06372v1 Announce Type: new<br \/>\nAbstract: We provide an upper bound on the number of neurons required in a shallow<br \/>\n  neural network to approximate a continuous function on a compact set with a<br \/>\n  given accuracy. This method, inspired by a specific proof of the<br \/>\n  Stone-Weierstrass theorem, is constructive and more general than previous<br \/>\n  bounds of this character, as it applies to any continuous function on any<br \/>\n  compact set.<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Frantisek Hakl, Vit Fojtik<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/arxiv.org\/abs\/2510.06372\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A General Constructive Upper Bound on Shallow Neural Nets Complexity arXiv:2510.06372v1 Announce Type: new Abstract: We provide an upper bound on the number of neurons required in a shallow neural network to approximate a continuous function on a compact set with a given accuracy. This method, inspired by a specific proof of the Stone-Weierstrass theorem, [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,113,112],"tags":[3979,1639,3980],"class_list":["post-7463","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-cs-lg","category-stat-ml","tag-constructive","tag-general","tag-upper"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/7463"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=7463"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/7463\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=7463"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=7463"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=7463"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}