BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.20//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:20180311T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20181104T060000
END:STANDARD
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
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20190409T150000
DTEND;TZID=America/New_York:20190409T160000
DTSTAMP:20260408T230424
CREATED:20190408T190332Z
LAST-MODIFIED:20190408T190332Z
UID:1553-1554822000-1554825600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Towards a New Synthesis of Reasoning and Learning"
DESCRIPTION:This talk discusses the role of logical reasoning in statistical machine learning. While their unification has been a long-standing and crucial open problem\, automated reasoning and machine learning are still disparate fields within artificial intelligence. I will describe recent progress towards their synthesis in three facets.\nI start with a very practical question: how can we enforce logical constraints on the output of deep neural networks to incorporate symbolic knowledge? Second\, I explain how circuits developed for tractable logical reasoning can be turned into statistical models. When brought to bear on a variety of machine learning tasks\, including discrete density estimation and simple image classification\, these probabilistic and logistic circuits yield state-of-the-art results. In a third facet\, I argue for high-level representations of uncertainty\, such as probabilistic programs\, probabilistic databases\, and statistical relational models. These pose unique challenges for inference that can only be overcome by high-level reasoning about their first-order structure to exploit symmetry and exchangeability.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-towards-a-new-synthesis-of-reasoning-and-learning/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
END:VCALENDAR