We will consider the problem of distributed cooperative non-Bayesian learning in a network of agents, where the agents are repeatedly gaining partial information about an unknown random variable whose distribution is to be jointly estimated. The joint objective of the agent system is to globally agree on a hypothesis (distribution) that best des...
Creator:
Nedich, Angelia (University of Illinois at Urbana-Champaign)
Created:
2015-10-02
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
The advances in wired and wireless technology necessitated the development of theory, models and tools to cope with new challenges posed by large-scale optimization problems over networks. The classical optimization works under the premise that all problem data is available to some central entity. This premise does not apply to large networked s...
Creator:
Nedich, Angelia (University of Illinois at Urbana-Champaign)
Created:
2014-06-03
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.