{"id":1150,"date":"2018-11-12T15:19:05","date_gmt":"2018-11-12T13:19:05","guid":{"rendered":"https:\/\/webs.uab.cat\/giq\/seminar\/classical-learning-theory-2\/"},"modified":"2018-11-12T15:19:05","modified_gmt":"2018-11-12T13:19:05","slug":"classical-learning-theory-2","status":"publish","type":"seminar","link":"https:\/\/webs.uab.cat\/giq\/seminar\/classical-learning-theory-2\/","title":{"rendered":"Classical Learning Theory"},"content":{"rendered":"<p>We will introduce the PAC learning framework for countable function classes. Then we will relax this constraint and consider two general approaches: growth functions and VC dimension (for binary labels).<\/p>\n<p>References: Michael Wolf&#8217;s <a href=\"http:\/\/www-m5.ma.tum.de\/Allgemeines\/MA4801_2018S\">notes<\/a> and references therein.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We will introduce the PAC learning framework for countable function classes. Then we will relax this constraint and consider two general approaches: growth functions and VC dimension (for binary labels). References: Michael Wolf&#8217;s notes and references therein.<\/p>\n","protected":false},"author":20,"featured_media":0,"template":"","class_list":["post-1150","seminar","type-seminar","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/seminar\/1150","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/seminar"}],"about":[{"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/types\/seminar"}],"author":[{"embeddable":true,"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/users\/20"}],"wp:attachment":[{"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/media?parent=1150"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}