Constrained stochastic gradient descent for large-scale least squares problem

  • Yang Mu
  • , Wei Ding
  • , Tianyi Zhou
  • , Dacheng Tao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationKDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
EditorsRajesh Parekh, Jingrui He, Dhillon S. Inderjit, Paul Bradley, Yehuda Koren, Rayid Ghani, Ted E. Senator, Robert L. Grossman, Ramasamy Uthurusamy
PublisherAssociation for Computing Machinery
Pages883-891
Number of pages9
ISBN (Electronic)9781450321747
DOIs
StatePublished - Aug 11 2013
Event19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013 - Chicago, United States
Duration: Aug 11 2013Aug 14 2013

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
VolumePart F128815

Conference

Conference19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013
Country/TerritoryUnited States
CityChicago
Period8/11/138/14/13

ASJC Scopus Subject Areas

  • Software
  • Information Systems

Keywords

  • Large-scale least squares
  • Online learning
  • Stochastic optimization

Fingerprint

Dive into the research topics of 'Constrained stochastic gradient descent for large-scale least squares problem'. Together they form a unique fingerprint.

Cite this