Scalable k -Means Clustering via Lightweight Coresets - Research Collection

Metadata only

Autor(in)

Bachem, Olivier

Krause, Andreas

Datum

2018

Typ

Conference Paper

Zitate

40 Zitate in Web of Science

44 Zitate in Scopus

ETH Bibliographie

yes

Altmetrics

Publikationsstatus

published

Externe Links

https://doi.org/10.1145/3219819.3219973

Buchtitel

KDD '18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Seiten / Artikelnummer

1119 - 1127

Verlag

ACM

Konferenz

24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2018), London, United Kingdom, August 19 - 23, 2018

Thema

Clustering; Coresets; Big data; Distributed algorithms

Organisationseinheit

03908 - Krause, Andreas / Krause, Andreas

Förderung

167212 - Scaling Up by Scaling Down: Big ML via Small Coresets (SNF)

307036 - Large-scale Adaptive Sensing, Learning and Decision Making: Theory and Applications (EC)

Anmerkungen

Conference lecture on 20 August 2018

Mehr

Alle Metadaten anzeigen

Zitate

40 Zitate in Web of Science

44 Zitate in Scopus

ETH Bibliographie

yes

Altmetrics