BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//wp-events-plugin.com//7.2.3.1//EN
TZID:Europe/Paris
X-WR-TIMEZONE:Europe/Paris
BEGIN:VEVENT
UID:5864@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20221125T143000
DTEND;TZID=Europe/Paris:20221125T153000
DTSTAMP:20241120T200641Z
URL:https://www.i2m.univ-amu.fr/evenements/clustering-approaches-for-tenso
 r-data/
SUMMARY:Rafika Boutalbi (LIS\, Aix-Marseille Université): Clustering appro
 aches for tensor data
DESCRIPTION:Rafika Boutalbi: Dealing with relational learning generally rel
 ies on tools modeling relational data. An undirected graph can represent t
 hese data with vertices depicting entities and edges describing the relati
 onships between the entities. These relationships can be well represented 
 by multiple undirected graphs over the same set of vertices\, with edges a
 rising from different graphs catching heterogeneous relations. The vertice
 s of those networks are often structured in unknown clusters with varying 
 properties of connectivity. These multiple graphs can be structured as a t
 hree-way tensor\, where each slice of tensor depicts a graph that is repre
 sented by a count data matrix. To extract relevant clusters\, I will prese
 nt a variety of model-based clustering capable of dealing with multiple gr
 aphs.\nRéunion Zoom:\nhttps://univ-amu-fr.zoom.us/j/97186539781?pwd=a3Q4Q
 04xMG85dmVUTW1ObHNaN0ZwUT09\n\nID de réunion : 971 8653 9781\nCode secre
 t : voir mail
ATTACH;FMTTYPE=image/jpeg:https://www.i2m.univ-amu.fr/wp-content/uploads/2
 022/10/Rafika_Boutalbi.png
CATEGORIES:Séminaire,Hybrid,Signal et Apprentissage
LOCATION:I2M Chateau-Gombert - CMI\, 39 Rue Joliot Curie\, Marseille\, 1301
 3\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=39 Rue Joliot Curie\, Marse
 ille\, 13013\, France;X-APPLE-RADIUS=100;X-TITLE=I2M Chateau-Gombert - CMI
 :geo:0,0
END:VEVENT
BEGIN:VTIMEZONE
TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
BEGIN:STANDARD
DTSTART:20221030T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
END:STANDARD
END:VTIMEZONE
END:VCALENDAR