BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Jim Halverson (Northeastern) DTSTART:20221121T131500Z DTEND:20221121T141500Z DTSTAMP:20260423T010637Z UID:MaML/4 DESCRIPTION:Title: Mac hine Learning for Pure Math\nby Jim Halverson (Northeastern) as part o f Mathematics and Machine Learning\n\n\nAbstract\nProgress in machine lear ning (ML) is poised to revolutionize a variety of STEM fields. But how cou ld these techniques — which are often stochastic\, error-prone\, and bla ckbox — lead to progress in pure mathematics\, which values rigor and un derstanding? I will exemplify how ML can be used to generate conjectures i n a Calabi-Yau singularity problem that is relevant for physics\, and will demonstrate how reinforcement learning can yield truth certificates that rigorously demonstrate properties of knots. The second half of the talk wi ll utilize ML theory instead of applied ML. Specifically\, I will develop a neural tangent kernel theory appropriate for flows in the space of metri cs (realized as neural networks)\, and will realize Perelman’s formulati on of Ricci flow as a specialization of the general theory.\n LOCATION:https://researchseminars.org/talk/MaML/4/ END:VEVENT END:VCALENDAR