{"id":759166,"date":"2021-06-29T11:14:45","date_gmt":"2021-06-29T18:14:45","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=759166"},"modified":"2021-07-08T11:19:08","modified_gmt":"2021-07-08T18:19:08","slug":"directions-in-ml-structured-models-for-automated-machine-learning","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/directions-in-ml-structured-models-for-automated-machine-learning\/","title":{"rendered":"Directions in ML: Structured Models for Automated Machine Learning"},"content":{"rendered":"<p>Automated machine learning (AutoML) seeks algorithmic methods for finding the best machine learning pipeline and hyperparameters to fit a new dataset. The complexity of this problem is astounding: viewed as an optimization problem, it entails search over an exponentially large space, with discrete and continuous variables. An efficient solution requires a strong structural prior on the optimization landscape of this problem.<\/p>\n<p>In this talk, we survey some of the most powerful techniques for AutoML on tabular datasets. We will focus in particular on techniques for meta-learning: how to quickly learn good models on a new dataset given good models for a large collection of datasets. We will see that remarkably simple structural priors, such as the low-dimensional structure used by the AutoML method Oboe, produce state-of-the-art results. The success of these simple models suggests that AutoML may be simpler than was previously understood.<\/p>\n<p>Learn more about the <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/aka.ms\/diml\">2020-2021 Directions in ML: AutoML and Automating Algorithms virtual speaker series ><span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Automated machine learning (AutoML) seeks algorithmic methods for finding the best machine learning pipeline and hyperparameters to fit a new dataset. The complexity of this problem is astounding: viewed as an optimization problem, it entails search over an exponentially large space, with discrete and continuous variables. An efficient solution requires a strong structural prior on [&hellip;]<\/p>\n","protected":false},"featured_media":759169,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"research-area":[13561,13556],"msr-video-type":[],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-759166","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-research-area-algorithms","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/zDx_jgb2eBk","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/759166"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/759166\/revisions"}],"predecessor-version":[{"id":759172,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/759166\/revisions\/759172"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/759169"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=759166"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=759166"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=759166"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=759166"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=759166"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=759166"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}