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DTSTART:20231029T030000
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UID:calendar.26191.field_data.0@www.diag.uniroma1.it
DTSTAMP:20260418T061153Z
CREATED:20230709T201449Z
DESCRIPTION: Titolo del seminarioVisual Analytics for eXplainable Deep Lear
 ning AbstractArtificial Intelligence\, in particular Deep Learning (DL)\, 
 has become pervasive in many domains in recent years. To help humans to un
 derstand the reasoning behind decisions or predictions made by the DL mode
 ls and improve their trustability\, the research field of eXplainable Deep
  Learning (XDL) has emerged. Visual Analytics (VA)\, defined as the scienc
 e of analytical reasoning supported by interactive visual interfaces\, is 
 a consolidated research discipline effectively applied to many different d
 omains. During the last five years\, Visual Analytics has provided several
  solutions supporting the emerging eXplainable Deep Learning field. This s
 eminar aims to present the basic notions of Visual Analytics and Deep Lear
 ning\, and then discuss how these two worlds have been merged to support t
 he emerging eXplainable Deep Learning\, showing the current state-of-the-a
 rt of the field.   Short BioGraziano Blasilli obtained a PhD in Engineerin
 g in Computer Science from Sapienza Università di Roma in 2022\, where is 
 currently a post-doctoral researcher. His research interests include Visua
 l Analytics applied to the cybersecurity domain and the eXplainable Artifi
 cial Intelligence field. He is part of the A.WA.RE Research Group (http://
 aware.diag.uniroma1.it/) led by Giuseppe Santucci.  Link per il seminario 
 on line: http://meet.google.com/mkk-dpix-usi
DTSTART;TZID=Europe/Paris:20230711T110000
DTEND;TZID=Europe/Paris:20230711T110000
LAST-MODIFIED:20230710T062422Z
LOCATION:Online. Google meet link: http://meet.google.com/mkk-dpix-usi
SUMMARY:Seminario pubblico di Graziano Blasilli (Procedura valutativa per n
 .1 posto di Ricercatore a tempo determinato tipologia A - SC 09/H1 SSD ING
 -INF/05) - Graziano Blasilli
URL;TYPE=URI:https://www.diag.uniroma1.it/node/26191
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