BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:America/New_York X-WR-TIMEZONE:America/New_York BEGIN:VEVENT UID:570@fds.yale.edu DTSTART;TZID=America/New_York:20230403T160000 DTEND;TZID=America/New_York:20230403T170000 DTSTAMP:20250916T142121Z URL:https://fds.yale.edu/events/sds-seminar-sebastian-pokutta-tu-berlin-co nditional-gradients-in-machine-learning/ SUMMARY:S&\;DS Seminar: Sebastian Pokutta (TU Berlin)\, "Conditional Gra dients in Machine Learning" DESCRIPTION:"Conditional Gradients in Machine Learning" \n\n\nSpeaker: Seba stian Pokutta (TU Berlin)\n\n\n\nMonday\, April 03\, 2023\, 4:00PM to 5:00 PM \n\n\n\n3:30pm - Pre-talk meet and greet teatime - Dana House\, 24 Hill house Avenue\n\n\n\nLocation: Mason Lab\, Rm. 211\, 9 Hillhouse Avenue New Haven\, CT 06511 or via Panopto\n\n\n\nAbstract: Conditional Gradient met hods are an important class of methods to minimize (non-)smooth convex fun ctions over (combinatorial) polytopes. Recently these methods received a l ot of attention as they allow for structured optimization and hence learni ng\, incorporating the underlying polyhedral structure into solutions. In this talk I will give a broad overview of these methods\, their applicatio ns\, as well as present some recent results both in traditional optimizati on and learning as well as in deep learning. \n\n\n\nSpeaker Bio: Sebastia n Pokutta is the Vice President of the Zuse Institute Berlin (ZIB) and a P rofessor of Mathematics at TU Berlin with a research focus on Artificial I ntelligence and Optimization. Having received both his diploma and Ph.D. i n mathematics from the University of Duisburg-Essen in Germany\, Pokutta w as a postdoctoral researcher and visiting lecturer at MIT\, worked for IBM ILOG\, and Krall Demmel Baumgarten. Prior to joining ZIB and TU Berlin\, he was the David M. McKenney Family Associate Professor in the School of I ndustrial and Systems Engineering and an Associate Director of the Machine Learning @ GT Center at the Georgia Institute of Technology as well as a Professor at the University of Erlangen-Nürnberg. Sebastian received the David M. McKenney Family Early Career Professorship in 2016\, an NSF CAREE R Award in 2015\, the Coca-Cola Early Career Professorship in 2014\, the o utstanding thesis award of the University of Duisburg-Essen in 2006\, as w ell as various Best Paper awards. \n\n\n\nPokutta’s research is situated at the intersection of Artificial Intelligence and Optimization\, combini ng Machine Learning with Discrete Optimization techniques as well as the T heory of Extended Formulations\, exploring the limits of computation in al ternative models of complexity. A particular focus are so-called Frank-Wol fe methods and conditional gradient methods due to their versatility in th e context of constrained optimization and structured learning. Pokutta has also worked on applications of Optimization and Machine Learning\, levera ging data in the context of pressing industrial and financial challenges. These areas include Supply Chain Management\, Manufacturing\, Cyber-Physic al Systems (incl. Industrial Internet\, Industry 4.0\, Internet of Things) \, and Finance. Examples of Pokutta’s applied work include stowage optim ization problems for inland vessels\, oil production problems\, clearing o f electricity markets\, order fulfillment problems\, warehouse location pr oblems\, simulation of autonomous vehicle fleets\, portfolio optimization problems\, optimal liquidity management strategies\, and predictive pregna ncy diagnostics. \n\n\n\n3:30pm - Pre-talk meet and greet teatime - Dana H ouse\, 24 Hillhouse Avenue\n CATEGORIES:FDS Events,Statistics & Data Science Seminar,Seminar Series END:VEVENT BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:DAYLIGHT DTSTART:20230312T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT END:DAYLIGHT END:VTIMEZONE END:VCALENDAR