A Penalty Alternating Direction Method Of Multipliers For Decentralized Composite Optimization

This video program is a part of the Premium package:

A Penalty Alternating Direction Method Of Multipliers For Decentralized Composite Optimization


  • IEEE MemberUS $11.00
  • Society MemberUS $0.00
  • IEEE Student MemberUS $11.00
  • Non-IEEE MemberUS $15.00
Purchase

A Penalty Alternating Direction Method Of Multipliers For Decentralized Composite Optimization

0 views
  • Share
This paper proposes a penalty alternating direction method of multipliers (ADMM) to minimize the summation of convex composite functions over a decentralized network. Each agent in the network holds a private function consisting of a smooth part and a non
This paper proposes a penalty alternating direction method of multipliers (ADMM) to minimize the summation of convex composite functions over a decentralized network. Each agent in the network holds a private function consisting of a smooth part and a non