{"id":44869,"date":"2023-03-06T13:26:46","date_gmt":"2023-03-06T18:26:46","guid":{"rendered":"https:\/\/engineering.jhu.edu\/ams\/?post_type=tribe_events&#038;p=44869"},"modified":"2023-03-06T13:26:46","modified_gmt":"2023-03-06T18:26:46","slug":"ams-weekly-seminar-assistant-professor-ben-grimmer","status":"publish","type":"tribe_events","link":"https:\/\/engineering.jhu.edu\/ams\/event\/ams-weekly-seminar-assistant-professor-ben-grimmer\/","title":{"rendered":"AMS Weekly Seminar | Assistant Professor Ben Grimmer"},"content":{"rendered":"<div>\n<p><strong><span>Location:\u00a0<\/span><\/strong><span>Gilman 132<\/span><\/p>\n<\/div>\n<div>\n<p><strong><span>When: <\/span><\/strong>March 9th\u00a0at 1:30 p.m.<span><\/span><\/p>\n<\/div>\n<div>\n<p><strong><span>Title: <\/span><\/strong>Scalable, Projection-Free Optimization Methods<\/p>\n<\/div>\n<div>\n<p><strong><span>Abstract:\u00a0<\/span><\/strong>We will introduce an approach to constrained optimization replacing orthogonal projections with much cheaper radial ones. This results in new first-order methods that are (i) scalable, sporting minimal per iteration costs, (ii) always yield fully feasible solutions, and (iii) applicable to a wide family of potentially nonconvex constraints. For example, when applied to linear programs, iteration costs amount to one matrix multiplication instead of more costly pivoting or matrix inverses. For semidefinite programming, iterations require computing one eigenvector, avoiding full decompositions. Beyond these classic settings, modern applications with nonconvex objectives and constraints will be discussed. The key mathematical insight underlying these methods is a new duality relating constrained optimization problems to unconstrained &#8220;radially dual&#8221; problems. From this, we will present accelerated projection-free first-order methods using smoothness, strong convexity, or other common structures in the primal objective or constraints.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Location:\u00a0Gilman 132 When: March 9th\u00a0at 1:30 p.m. Title: Scalable, Projection-Free Optimization Methods Abstract:\u00a0We will introduce an approach to constrained optimization replacing orthogonal projections with much cheaper radial ones. This results&hellip;<\/p>\n","protected":false},"author":69,"featured_media":0,"template":"","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[260],"class_list":["post-44869","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-seminars-and-endowed-lectures","cat_seminars-and-endowed-lectures"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AMS Weekly Seminar | Assistant Professor Ben Grimmer | Department of Applied Mathematics and Statistics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/engineering.jhu.edu\/ams\/event\/ams-weekly-seminar-assistant-professor-ben-grimmer\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AMS Weekly Seminar | Assistant Professor Ben Grimmer | Department of Applied Mathematics and Statistics\" \/>\n<meta property=\"og:description\" content=\"Location:\u00a0Gilman 132 When: March 9th\u00a0at 1:30 p.m. Title: Scalable, Projection-Free Optimization Methods Abstract:\u00a0We will introduce an approach to constrained optimization replacing orthogonal projections with much cheaper radial ones. This results&hellip;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/engineering.jhu.edu\/ams\/event\/ams-weekly-seminar-assistant-professor-ben-grimmer\/\" \/>\n<meta property=\"og:site_name\" content=\"Department of Applied Mathematics and Statistics\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"AMS Weekly Seminar | Assistant Professor Ben Grimmer | Department of Applied Mathematics and Statistics","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/engineering.jhu.edu\/ams\/event\/ams-weekly-seminar-assistant-professor-ben-grimmer\/","og_locale":"en_US","og_type":"article","og_title":"AMS Weekly Seminar | Assistant Professor Ben Grimmer | Department of Applied Mathematics and Statistics","og_description":"Location:\u00a0Gilman 132 When: March 9th\u00a0at 1:30 p.m. Title: Scalable, Projection-Free Optimization Methods Abstract:\u00a0We will introduce an approach to constrained optimization replacing orthogonal projections with much cheaper radial ones. 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