Amanote Research

Amanote Research

  • Register
  • Sign In

Distributed Subgradient Algorithm for Multi-Agent Convex Optimization With Local Constraint Sets

Applied and Computational Mathematics

doi 10.11648/j.acm.20160503.19

Full Text

Abstract

Available in

Date

January 1, 2016

Authors

Qingguo Lü

Publisher

Science Publishing Group


Related search

Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets

Proceedings of the AAAI Conference on Artificial Intelligence
2019English

Distributed Optimization of Multi-Agent Systems: Framework, Local Optimizer, and Applications

English

Logarithmic Communication for Distributed Optimization in Multi-Agent Systems

Proceedings of the ACM on Measurement and Analysis of Computing Systems
2019English

A Novel Distributed Scheduling Algorithm for Time-Critical Multi-Agent Systems

2015English

A New Hybrid Distributed Double Guided Genetic Swarm Algorithm for Optimization and Constraint Reasoning

International Journal of Swarm Intelligence Research
Computational TheoryComputer Science ApplicationsArtificial IntelligenceMathematics
2012English

Continuous-Time Distributed Convex Optimization With Set Constraints

IFAC Proceedings Volumes
2014English

Asynchronous Newton-Raphson Consensus for Distributed Convex Optimization*

IFAC Proceedings Volumes
2012English

A New Simultaneous Subgradient Projection Algorithm for Solving a Multiple-Sets Split Feasibility Problem

Applications of Mathematics
Applied Mathematics
2014English

Strategies for Distributed Sensor Selection Using Convex Optimization

2012English

Amanote Research

Note-taking for researchers

Follow Amanote


© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy