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BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Penn Engineering Events - ECPv6.18.0//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Penn Engineering Events X-ORIGINAL-URL:https://seasevents.nmsdev7.com X-WR-CALDESC:Events for Penn Engineering Events REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20190310T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20191103T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20200308T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20201101T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20210314T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20211107T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20201027T150000 DTEND;TZID=America/New_York:20201027T160000 DTSTAMP:20201022T173327Z CREATED:20201022T173327Z LAST-MODIFIED:20201022T173327Z UID:3597-1603810800-1603814400@seasevents.nmsdev7.com SUMMARY:CIS Seminar: "Advances in Machine Learning Systems Research" DESCRIPTION:A long-standing grand challenge in computing is to enable machines to act autonomously and intelligently: to rapidly and repeatedly take appropriate actions based on information in the world around them. Driven by trends in the data economy\, rapid progress in AI\, and an increasingly programmable physical world we are at an inflection point that demands a new class of AI system. This new class of systems goes beyond training models at scale\, to connecting models with the world\, rendering predictions in real-time under heavy query load\, adapting to new observations and contexts. These systems will need to be composable and elastically scalable to accommodate new technologies and variations in workloads. Operating in the physical world\, observing intimate details of our lives\, and making critical decisions\, these systems must also be secure. \nIn this talk\, I will present work in my group exploring advances in systems for prediction serving\, autonomous driving\, and how model design and system design interact.  In particular\, I will discuss some of the key trade-offs between time\, accuracy\,  convergence\, throughput\, and security that govern how we design systems\, train models\, and make predictions that meet the demands of real-world applications. URL:https://seasevents.nmsdev7.com/event/cis-seminar-advances-in-machine-learning-systems-research/ LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu END:VEVENT END:VCALENDAR