par Coppens, Youri ;Shirahata, Koichi;Fukagai, Takuya;Tomita, Yasumoto;Ike, Atsushi
Référence 2017 Fifth International Symposium on Computing and Networking (CANDAR)(19-22 Nov. 2017: Aomori, Japan), 2017 Fifth International Symposium on Computing and Networking (CANDAR), IEEE, page (330-336)
Publication Publié, 2017-11-19
Publication dans des actes
Titre:
  • GUNREAL: GPU-accelerated UNsupervised REinforcement and Auxiliary Learning
Auteur:Coppens, Youri; Shirahata, Koichi; Fukagai, Takuya; Tomita, Yasumoto; Ike, Atsushi
Informations sur la publication:2017 Fifth International Symposium on Computing and Networking (CANDAR)(19-22 Nov. 2017: Aomori, Japan), 2017 Fifth International Symposium on Computing and Networking (CANDAR), IEEE, page (330-336)
Statut de publication:Publié, 2017-11-19
Sujet CREF:Intelligence artificielle
Mots-clés:Acceleration,Actor-Critic algorithm,Asynchronous Computation,Deep Reinforcement Learning,GPU,Graphics processing units,Instruction sets,Machine Learning,Machine learning,Servers,Task analysis,Training
Langue:Anglais
Identificateurs:urn:isbn:978-1-5386-2087-8
info:doi/10.1109/CANDAR.2017.27