{"id":2581,"date":"2022-01-28T10:36:38","date_gmt":"2022-01-28T18:36:38","guid":{"rendered":"https:\/\/colleges.claremont.edu\/ccms\/?post_type=tribe_events&p=2581"},"modified":"2022-01-31T11:35:06","modified_gmt":"2022-01-31T19:35:06","slug":"exploiting-metric-structure-for-more-accurate-classification-prof-mike-izbicki","status":"publish","type":"tribe_events","link":"https:\/\/colleges.claremont.edu\/ccms\/event\/exploiting-metric-structure-for-more-accurate-classification-prof-mike-izbicki\/","title":{"rendered":"Exploiting metric structure for more accurate classification (Prof. Mike Izbicki)"},"content":{"rendered":"

Title:<\/strong> Exploiting metric structure for more accurate classification<\/p>\n

Speaker:<\/strong>\u00a0Mike Izbicki, Department of Mathematical Sciences, Claremont McKenna College<\/p>\n

Abstract:\u00a0<\/strong>Classification problems often have many semantically similar classes.\u00a0 For\u00a0example, the famous ImageNet dataset contains classes for 80 different dog breeds, 40 different bird species, and 25 types of vehicles.\u00a0 This semantic structure can be formalized using a metric space, with semantic similarity of\u00a0classes encoded by the distance function.\u00a0 In this talk, I’ll describe the “tree loss”, which is the first technique with provable performance guarantees for exploiting this metric structure.\u00a0 I’ll also show that the tree loss has better empirical performance than competing algorithms on image, text, and vector data.<\/p>\n

\n
Mike studies machine learning theory, focusing on applications to natural\u00a0language and social media.\u00a0\u00a0He has been at CMC for 3 years now, where he teaches\u00a0computer and data science classes.\u00a0\u00a0Prior to his academic career, Mike spent 7\u00a0years in the US Navy.\u00a0\u00a0Highlights include converting >10g of Uranium into pure\u00a0energy as a nuclear submarine officer, and doing [redacted] for the NSA.\u00a0\u00a0After\u00a0leaving the navy, Mike went to North Korea to teach computer science as part of\u00a0an academic exchange program designed to improve relations between the US and\u00a0North Korea.\u00a0\u00a0He earned his phd from UC Riverside.<\/div>\n","protected":false},"excerpt":{"rendered":"

Title: Exploiting metric structure for more accurate classification Speaker:\u00a0Mike Izbicki, Department of Mathematical Sciences, Claremont McKenna College Abstract:\u00a0Classification problems often have many semantically similar classes.\u00a0 For\u00a0example, the famous ImageNet dataset […]<\/p>\n","protected":false},"author":165,"featured_media":0,"template":"","meta":{"_acf_changed":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","footnotes":"","_tec_slr_enabled":"","_tec_slr_layout":""},"tags":[],"tribe_events_cat":[12],"class_list":["post-2581","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-colloquium","cat_colloquium"],"acf":[],"yoast_head":"\nExploiting metric structure for more accurate classification (Prof. Mike Izbicki) - Claremont Center for the Mathematical Sciences<\/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:\/\/colleges.claremont.edu\/ccms\/event\/exploiting-metric-structure-for-more-accurate-classification-prof-mike-izbicki\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Exploiting metric structure for more accurate classification (Prof. Mike Izbicki) - Claremont Center for the Mathematical Sciences\" \/>\n<meta property=\"og:description\" content=\"Title: Exploiting metric structure for more accurate classification Speaker:\u00a0Mike Izbicki, Department of Mathematical Sciences, Claremont McKenna College Abstract:\u00a0Classification problems often have many semantically similar classes.\u00a0 For\u00a0example, the famous ImageNet dataset […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/colleges.claremont.edu\/ccms\/event\/exploiting-metric-structure-for-more-accurate-classification-prof-mike-izbicki\/\" \/>\n<meta property=\"og:site_name\" content=\"Claremont Center for the Mathematical Sciences\" \/>\n<meta property=\"article:modified_time\" content=\"2022-01-31T19:35:06+00:00\" \/>\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<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/colleges.claremont.edu\/ccms\/event\/exploiting-metric-structure-for-more-accurate-classification-prof-mike-izbicki\/\",\"url\":\"https:\/\/colleges.claremont.edu\/ccms\/event\/exploiting-metric-structure-for-more-accurate-classification-prof-mike-izbicki\/\",\"name\":\"Exploiting metric structure for more accurate classification (Prof. Mike Izbicki) - 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