BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Etis - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.etis-lab.fr
X-WR-CALDESC:Events for Etis
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20240331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20241027T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20251026T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20250220T144500
DTEND;TZID=Europe/Paris:20250220T163000
DTSTAMP:20260422T024707
CREATED:20250210T100905Z
LAST-MODIFIED:20250210T100905Z
UID:8995-1740062700-1740069000@www.etis-lab.fr
SUMMARY:ETIS Tandem Talk: Paul Gay & Guillaume Renton
DESCRIPTION:Tandem Talk by Paul Gay (UPPA) and Guillaume Renton (ETIS) on Sustainability and Machine Learning. \nPaul Gay | Interactions between sustainibility and machine learning research\nAI is a controversial topic and different visions of sustainibility co-exist in the IT communities. In this talk\, I will describe the state of the art from the GreenIT community to assess environmental impact of IT projects. Although the main ideas\, such as life cycle analysis\, description of embodied impacts and indirect effects have been explored for 10-20 years\, we are only beginning to see them applied to AI systems and projects. \nIn a second part\, I will present two of my current machine learning applications to sustainibility topics. The first one is the use of active learning to detect and classify controversial topic on renewable energies in social networks. The second one is to exploit the technique of early exit\, an interesting tool where the amount of compute depends on the data\, and which find applications in edge-cloud settings. \nGuillaume Renton | Reducing computation costs without jeopardizing precision of Entity Alignment tasks\nIn recent work\, we took interest in the computational cost of one of our entity alignment model\, HybEA. The idea was to provide an efficiency analysis on top of a performance analysis\, which is the main source of comparison between AI models. The efficiency analysis was conducted by using fvcore in order to compute the number of GFLOPS required to train the model. This has led to surprising results\, showing that the initial embedding sizes of the models were oversized. This allowed us to greatly reduce the computational cost of our model with a very small loss of accuracy. \n  \nThe talks will take place in the Curium at ENSEA as well as online:\nhttps://cnrs.zoom.us/j/92031778182?pwd=BcsbEGTQf2JwG8jIUkpaK35fZ1WXUK.1
URL:https://www.etis-lab.fr/event/etis-tandem-talk-paul-gay-guillaume-renton/
LOCATION:ENSEA\, Curium\, avenue du Ponceau\, Cergy\, 95014\, France
CATEGORIES:ETIS,Seminar
ORGANIZER;CN="Camille Simon Chane":MAILTO:camille.simon-chane@ensea.fr
END:VEVENT
END:VCALENDAR