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Distributed optimization for cooperative agents: Application to formation flight
Distributed algorithm optimization communication dual duality
2015/8/11
We present a simple decentralized algorithm to solve optimization problems involving cooperative agents. Cooperative agents share a common objective and simultaneously pursue private goals. Furthermor...
Distributed optimization and statistical learning via the alternating direction method of multipliers
Statistics machine learning convex optimization framework modern data set data set
2015/8/7
Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasi...
Block splitting for distributed optimization
Distributed computing convex optimization data large linear operator matrix machine
2015/8/7
This paper describes a general purpose method for solving convex optimization problems in a distributed computing environment. In particular, if the problem data includes a large linear operator or ma...
Distributed Optimization for Cooperative Agents: Application to Formation Flight
Distributed Optimization Cooperative Agents Application Formation Flight
2015/7/10
We present a simple decentralized algorithm to solve optimization problems involving cooperative agents. Cooperative agents share a common objective and simultaneously pursue private goals. Furthermor...
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
Distributed Optimization Statistical Learning via Alternating Direction Method Multipliers
2015/7/9
Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasi...
Block Splitting for Distributed Optimization
Distributed optimization · Alternating direction method of multipliers Operator splitting Proximal operators Cone programming Machine learning
2015/7/9
This paper describes a general purpose method for solving convex optimization problems in a distributed computing environment. In particular, if the problem data includes a large linear operator or ma...