Incremental subgradient methods for nondifferentiable optimization

Angelia Geary, Dimitri P. Bertsekas

Research output: Contribution to journalConference articlepeer-review

10 Scopus citations


Proposed is a new class of subgradient methods for minimizing a convex function that consists of the sum of a large number of component functions. The convergence properties of a number of variants of incremental subgradient methods are established. Based on the analysis and computational experiments, the methods appear very promising and effective for important classes of large problems.

Original languageEnglish (US)
Pages (from-to)907-912
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 1999
Externally publishedYes
EventThe 38th IEEE Conference on Decision and Control (CDC) - Phoenix, AZ, USA
Duration: Dec 7 1999Dec 10 1999

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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