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Pushing AI out of the lab with on-the-fly mixture domain adaptation

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Pierard, Sébastien Cioppa, Anthony Halin, Anaïs Vandeghen, Renaud Zanella, Maxime [UCL] Macq, Benoît [UCL]

Posteriors are relative to a domain.• Source: domains for which it is possible to have data to train ML/AI models.• Target: domains in which the models are used, usually unknown in advance.• Domains are a cornerstone to interpret the posteriors and make the right decisions!

Document type Communication à un colloque (Conference Paper) – Présentation orale avec comité de sélection
Access type Accès libre
Publication date 2023
Language Anglais
Conference "The European AI Week", Brussels, Belgium (du 27/03/2023 au 31/03/2023)
Affiliation UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique
Links
Bibliographic reference Pierard, Sébastien ; Cioppa, Anthony ; Halin, Anaïs ; Vandeghen, Renaud ; Zanella, Maxime ; et. al. Pushing AI out of the lab with on-the-fly mixture domain adaptation.The European AI Week (Brussels, Belgium, du 27/03/2023 au 31/03/2023).
Permanent URL http://hdl.handle.net/2078.1/283086