{"id":691,"date":"2025-03-08T13:13:45","date_gmt":"2025-03-08T12:13:45","guid":{"rendered":"https:\/\/www.evostar.org\/2025\/?page_id=691"},"modified":"2025-03-08T13:22:44","modified_gmt":"2025-03-08T12:22:44","slug":"evolutionary-machine-learning-accepted-papers","status":"publish","type":"page","link":"https:\/\/www.evostar.org\/2025\/evolutionary-machine-learning-accepted-papers\/","title":{"rendered":"Evolutionary Machine Learning Accepted Papers"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Long talks<\/h2>\n\n\n\n<li>Social Interpretable Reinforcement Learning<br><em>Leonardo Lucio Custode and Giovanni Iacca<\/em><\/li>\n<li>EDCA &#8211; An Evolutionary Data-Centric AutoML Framework for Efficient Pipelines<br><em>Joana Sim\u00f5es and Jo\u00e3o Correia<\/em><\/li>\n<li>Generate more than one child in your co-evolutionary semi-supervised learning GAN<br><em>Francisco Jos\u00e9 Sede\u00f1o, Jamal Toutouh and Francisco Chicano<\/em><\/li>\n<li>Evolving RNNs for Stock Forecasting: A Low Parameter Efficient Alternative to Transformers<br><em>Zimeng Lyu, Devroop Kar, Matthew Simoni, Rohaan Nadeem, Avinash Bhojanapalli, Hao Zhang and Travis Desell<\/em><\/li>\n<li>Into the Black Box: Mining Variable Importance with XAI<br><em>Kelly Hunter, Sarah L. Thomson and Emma Hart<\/em><\/li>\n\n\n\n<h2 class=\"wp-block-heading\">Short talk<\/h2>\n\n\n\n<li>Micro-Step Time-Series Regression: Insights from System Identification Using Symbolic Regression<br><em>Hengzhe Zhang, Alberto Tonda, Qi Chen, Bing Xue, Evelyne Lutton and Mengjie Zhang<\/em><\/li>\n","protected":false},"excerpt":{"rendered":"<p>Long talks Social Interpretable Reinforcement LearningLeonardo Lucio Custode and Giovanni Iacca EDCA &#8211; An Evolutionary Data-Centric AutoML Framework for Efficient PipelinesJoana Sim\u00f5es and Jo\u00e3o Correia Generate more than one child in your co-evolutionary semi-supervised learning GANFrancisco Jos\u00e9 Sede\u00f1o, Jamal Toutouh and Francisco Chicano Evolving RNNs for Stock Forecasting: A Low Parameter Efficient Alternative to TransformersZimeng [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-691","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.evostar.org\/2025\/wp-json\/wp\/v2\/pages\/691","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.evostar.org\/2025\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.evostar.org\/2025\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.evostar.org\/2025\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.evostar.org\/2025\/wp-json\/wp\/v2\/comments?post=691"}],"version-history":[{"count":2,"href":"https:\/\/www.evostar.org\/2025\/wp-json\/wp\/v2\/pages\/691\/revisions"}],"predecessor-version":[{"id":706,"href":"https:\/\/www.evostar.org\/2025\/wp-json\/wp\/v2\/pages\/691\/revisions\/706"}],"wp:attachment":[{"href":"https:\/\/www.evostar.org\/2025\/wp-json\/wp\/v2\/media?parent=691"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}