BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Afonso Bandeira (ETH Zurich) DTSTART:20200604T163000Z DTEND:20200604T173000Z DTSTAMP:20260423T003301Z UID:MPML/2 DESCRIPTION:Title: Com putation\, statistics\, and optimization of random functions\nby Afons o Bandeira (ETH Zurich) as part of Mathematics\, Physics and Machine Learn ing (IST\, Lisbon)\n\n\nAbstract\nWhen faced with a data analysis\, learni ng\, or statistical inference problem\, the amount and quality of data ava ilable fundamentally determines whether such tasks can be performed with c ertain levels of accuracy. Indeed\, many theoretical disciplines study lim its of such tasks by investigating whether a dataset effectively contains the information of interest. With the growing size of datasets however\, i t is crucial not only that the underlying statistical task is possible\, b ut also that is doable by means of efficient algorithms. In this talk we w ill discuss methods aiming to establish limits of when statistical tasks a re possible with computationally efficient methods or when there is a fund amental Statistical-to-Computational gap in which an inference task is sta tistically possible but inherently computationally hard.\n\nThis is intima tely related to understanding the geometry of random functions\, with conn ections to statistical physics\, study of spin glasses\, random geometry\; and in an important example\, algebraic invariant theory.\n LOCATION:https://researchseminars.org/talk/MPML/2/ END:VEVENT END:VCALENDAR