{"id":13017,"date":"2024-04-02T08:02:06","date_gmt":"2024-04-02T08:02:06","guid":{"rendered":"https:\/\/dei.fe.up.pt\/dev\/?p=13017"},"modified":"2024-04-02T08:02:18","modified_gmt":"2024-04-02T08:02:18","slug":"synthetic-data-for-a-better-understanding-of-models-and-algorithms-by-carlos-soares","status":"publish","type":"post","link":"https:\/\/dei.fe.up.pt\/dev\/synthetic-data-for-a-better-understanding-of-models-and-algorithms-by-carlos-soares\/","title":{"rendered":"&#8220;Synthetic data for a better understanding of models and algorithms&#8221; by Carlos Soares"},"content":{"rendered":"<p>The generation of synthetic data has gained a lot of relevance, particularly to provide more data for learning models, for example with GANs (Generative Adversarial Networks), which are effective and have a relatively simple implementation method, making them one of the most widely used methodologies for generating synthetic data. However, (semi-)synthetic data is also relevant to an even more important task, which is to improve our understanding of the behaviour of ML (Machine Learning) models and algorithms.<\/p>\n<p><strong><a href=\"https:\/\/www.linkedin.com\/in\/cpsoares\/\">Carlos Soares<\/a><\/strong>, Professor at DEI and researcher in this area, invited by the <strong><em>Universit\u00e0 degli Studi di Bari Aldo Moro<\/em><\/strong> (Italy) to integrate a doctoral jury, also gave in this institution a seminar on <strong>March 26<sup>th<\/sup><\/strong> entitled &#8220;<strong>Synthetic data for a better understanding of models and algorithms<\/strong>&#8220;, addressing\u00a0 limitations of current research practices in Machine Learning \/AI, describing some of the work underway at FEUP with the aim of improving these practices, within the scope of projects such as the <strong><a href=\"https:\/\/centerforresponsible.ai\/research\/\">Center for Responsible AI<\/a><\/strong> and <strong><a href=\"https:\/\/aisym4med.eu\/\">AISym4Med<\/a><\/strong>.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The generation of synthetic data has gained a lot of relevance, particularly to provide more data for learning models, for example with GANs (Generative Adversarial Networks), which are effective and have a relatively simple implementation method, making them one of the most widely used methodologies for generating synthetic data. However, (semi-)synthetic data is also relevant [&hellip;]<\/p>\n","protected":false},"author":60,"featured_media":13015,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[267,27],"tags":[],"class_list":["post-13017","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-highlights","category-news"],"_links":{"self":[{"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/posts\/13017","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/users\/60"}],"replies":[{"embeddable":true,"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/comments?post=13017"}],"version-history":[{"count":1,"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/posts\/13017\/revisions"}],"predecessor-version":[{"id":13018,"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/posts\/13017\/revisions\/13018"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/media\/13015"}],"wp:attachment":[{"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/media?parent=13017"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/categories?post=13017"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dei.fe.up.pt\/dev\/wp-json\/wp\/v2\/tags?post=13017"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}