Empirically explaining SGD from a line search perspective

dc.contributor.author	Mutschler, Maximus
dc.contributor.author	Zell, Andreas
dc.date.accessioned	2021-10-15T15:30:34Z
dc.date.available	2021-10-15T15:30:34Z
dc.date.issued	2021-09-07
dc.identifier.isbn	978-3-030-86339-5
dc.identifier.uri	http://hdl.handle.net/10900/119777
dc.language.iso	en	de_DE
dc.publisher	Cham : Springer	de_DE
dc.relation.ispartofseries	Lecture Notes in Computer Science;12892
dc.relation.uri	https://doi.org/10.1007/978-3-030-86340-1_37	de_DE
dc.subject.ddc	004	de_DE
dc.title	Empirically explaining SGD from a line search perspective	de_DE
dc.type	BookPart	de_DE
dc.type	ConferenceObject	de_DE
utue.publikation.seiten	459-471	de_DE
utue.personen.roh	Mutschler, Maximus
utue.personen.roh	Zell, Andreas
utue.publikation.buchdesbeitrags	Farkaš, I., Masulli, P., Otte, S., Wermter, S. (Hrsg.): Artificial Neural Networks and Machine Learning – ICANN 2021	de_DE