Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 336

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A Randomized Incremental Subgradient Method for Distributed Optimization in Networked Systems

Johansson, Björn, Rabi, Maben, Johansson, Mikael·2010·SIAM Journal on Optimization

Abstract

We present an algorithm that generalizes the randomized incremental subgradient method with fixed stepsize due to Nedić and Bertsekas [SIAM J. Optim., 12 (2001), pp. 109–138]. Our novel algorithm is particularly suitable for distributed implementation and execution, and possible applications include distributed optimization, e.g., parameter estimation in networks of tiny wireless sensors. The stochastic component in the algorithm is described by a Markov chain, which can be constructed in a distributed fashion using only local information. We provide a detailed convergence analysis of the proposed algorithm and compare it with existing, both deterministic and randomized, incremental subgradient methods.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1137/08073038x

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 336

Metadata

Authors
Johansson, B., Rabi, M., & Johansson, M.
Venue
SIAM Journal on Optimization
Published
2010-01
Volume
20
Issue
3
Pages
1157-1170
ISSN
  • 1052-6234 (ISSN-L)
  • 1095-7189
OpenAlex
W2049659086
Cited by
336
References
1
FWCI
22.65
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A Randomized Incremental Subgradient Method for Distributed Optimization in Networked Systems. https://app.cochat.ai/papers/10.1137/08073038x
The paper
Johansson, B., Rabi, M., & Johansson, M. (2010). A Randomized Incremental Subgradient Method for Distributed Optimization in Networked Systems. SIAM Journal on Optimization. https://doi.org/10.1137/08073038x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.