Efficient Hessian-based DNN Optimization via Chain-Rule Approximation

Reference : Efficient Hessian-based DNN Optimization via Chain-Rule Approximation


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/54533

Title :	Efficient Hessian-based DNN Optimization via Chain-Rule Approximation
Language :	English
Author, co-author :	Temperoni, Alessandro [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)]
	Dalle Lucca Tosi, Mauro [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)]
	Theobald, Martin [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)]
Publication date :	2023
Main document title :	Proceedings of the 6th Joint International Conference on Data Science Management of Data (10th ACM IKDD CODS and 28th COMAD)
Pages :	297--298
Peer reviewed :	Yes
Audience :	International
Event name :	6th Joint International Conference on Data Science & Management of Data
Event date :	from 04-01-2023 to 07-01-2023
Permalink :	http://hdl.handle.net/10993/54533
FnR project :	FnR ; FNR12252781 > Andreas Zilian > DRIVEN > Data-driven Computational Modelling And Applications > 01/09/2018 > 28/02/2025 > 2017

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