Decentralized Optimization for Multi-Agent Networks Qing Ling - PowerPoint PPT Presentation

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Decentralized Optimization for Multi-Agent Networks Qing Ling Department of Automation, University of Science and Technology of China (USTC) Joint work with Wotao Yin (UCLA), Wei Shi and Kun Yuan (USTC) 2014 Workshop on Optimization for Modern

Decentralized Optimization for Multi-Agent Networks Qing Ling Department of Automation, University of Science and Technology of China (USTC) Joint work with Wotao Yin (UCLA), Wei Shi and Kun Yuan (USTC) 2014 Workshop on Optimization for Modern Computation 2014/09/02 1
Outline 2
Multi-agent networks 3
Decentralized consensus optimization 4
Example: target localization 5
Decentralized versus distributed optimization 6
Related work 7
Assumptions 8
Decentralized gradient descent (DGD) 9
Mixing matrix 10
Existing convergence analysis 11
Can we reach consensus? 12
Essence of DGD 13
When gradients are bounded? 14
Where to converge and how fast? 15
Concluding DGD 16
EXact firsT-ordeR Algorithm (EXTRA) 17
Mixing matrices 18
Limit properties 19
Explanations of EXTRA 20
Sublinear convergence 21
Linear convergence 22
Simulation settings 23
Simulation of DGD and EXTRA 24
Concluding EXTRA 25
Future research directions 26
Thank you 27

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