BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.16.3//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:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250225T140000
DTEND;TZID=America/New_York:20250225T150000
DTSTAMP:20260602T144936
CREATED:20250122T143010Z
LAST-MODIFIED:20250122T143010Z
UID:12942-1740492000-1740495600@seasevents.nmsdev7.com
SUMMARY:Spring 2025 GRASP Seminar: Erdem Bıyık\, University of Southern California\, “Robot Learning with Minimal Human Feedback”
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nThe lack of large robotics datasets is arguably the most important obstacle in front of robot learning. While large pretrained models and algorithms like reinforcement learning from human feedback led to breakthroughs in other domains like language and vision\, robotics has not experienced such a significant influence due to the excessive cost of collecting large datasets. In this talk\, I will discuss techniques that enable us to train robots from very little human feedback\, as little as one demonstration or one language instruction\, or their natural eye gaze. I will dive into reinforcement learning from human feedback\, and propose an alternative type of human feedback based on language corrections to improve data-efficiency. I will finalize my talk by presenting how existing large pretrained vision-language models can be used to generate direct supervision for robot learning.
URL:https://seasevents.nmsdev7.com/event/spring-2025-grasp-seminar-erdem-biyik-university-of-southern-california-robot-learning-with-minimal-human-feedback/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
END:VCALENDAR