{"id":3393,"date":"2023-10-11T13:54:20","date_gmt":"2023-10-11T18:54:20","guid":{"rendered":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/?post_type=tribe_events&#038;p=3393"},"modified":"2023-10-11T13:54:20","modified_gmt":"2023-10-11T18:54:20","slug":"lans-seminar-111","status":"publish","type":"tribe_events","link":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/event\/lans-seminar-111\/","title":{"rendered":"LANS Seminar"},"content":{"rendered":"<p><strong>Seminar Title:\u00a0<\/strong>A scalable method to exploit screening in Gaussian process models with noise<\/p>\n<p><strong>Speaker:\u00a0<\/strong>Chris Geoga, Assistant Professor, Department of Statistics UW Madison<\/p>\n<p><strong>Date\/Time:<\/strong>\u00a0October 25, 2023\/10:30 AM-11:30 AM<\/p>\n<p><strong>Location:<\/strong> <em>See Meeting URL on the Cels-seminars website which requires an Argonne login.<\/em><\/p>\n<p><strong>Host:<\/strong>\u00a0Adrian Maldonado<\/p>\n<p><strong>Treats and Coffee:\u00a0<\/strong>10 AM Provided by Jeffrey Larson<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Description:<\/strong>\u00a0A common approach to approximating Gaussian log-likelihoods at scale exploits the fact that precision matrices can be well-approximated by sparse matrices in some circumstances. This strategy is motivated by the\u00a0<em data-stringify-type=\"italic\">screening effect<\/em>, which refers to the phenomenon in which the linear prediction of a process\u00a0<em data-stringify-type=\"italic\">Z<\/em>\u00a0at a point x0 depends primarily on measurements nearest to x0. But simple perturbations, such as iid measurement noise, can significantly reduce the degree to which this exploitable phenomenon occurs. While strategies to cope with this issue already exist and are certainly improvements over ignoring the problem, in this work we present a new one based on the EM algorithm that offers several advantages. While in this work we focus on the application to Vecchia\u2019s approximation (Vecchia), a particularly popular and powerful framework in which we can demonstrate true second-order optimization of M steps, the method can also be applied using entirely matrix-vector products, making it applicable to a very wide class of precision matrix-based approximation methods.<\/p>\n<p><strong>Bio:<\/strong>\u00a0Chris Geoga is an assistant professor at UW Madison\u2019s Department of Statistics. He completed his PhD in statistics at Rutgers University in 2023, advised by Michael L. Stein. Chris is interested in a broad range of topics at the intersection of applied mathematics, computing, and statistics, and works with large-scale Gaussian process models to study complex dependence structure in environmental data. From 2016 to 2018, Chris was also an RD1 in the Math and Computer Science Division at ANL, supervised by Mihai Anitescu.<\/p>\n<p><em>Please not that the meeting URL for this event can be seen on the Cels-seminars website which requires an Argonne login.<\/em><\/p>\n<p>See all upcoming talks at\u00a0<a href=\"https:\/\/www.anl.gov\/mcs\/lans-seminars\">https:\/\/www.anl.gov\/mcs\/lans-seminars<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Seminar Title:\u00a0A scalable method to exploit screening in Gaussian process models with noise Speaker:\u00a0Chris Geoga, Assistant Professor, Department of Statistics UW Madison Date\/Time:\u00a0October 25, 2023\/10:30 AM-11:30 AM Location: See Meeting URL on the Cels-seminars website which requires an Argonne login. &hellip; <a href=\"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/event\/lans-seminar-111\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":976,"featured_media":0,"template":"","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[],"class_list":["post-3393","tribe_events","type-tribe_events","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events\/3393","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/users\/976"}],"version-history":[{"count":2,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events\/3393\/revisions"}],"predecessor-version":[{"id":3396,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events\/3393\/revisions\/3396"}],"wp:attachment":[{"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/media?parent=3393"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tags?post=3393"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/wordpress.cels.anl.gov\/lans-seminars\/wp-json\/wp\/v2\/tribe_events_cat?post=3393"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}