Distributed Non-Stochastic Experts
–Neural Information Processing Systems
We consider the online distributed non-stochastic experts problem, where the distributed system consists of one coordinator node that is connected to k sites, and the sites are required to communicate with each other via the coordinator. At each time-step t, one of the k site nodes has to pick an expert from the set {1,..., n}, and the same site receives information about payoffs of all experts for that round. The goal of the distributed system is to minimize regret at time horizon T, while simultaneously keeping communication to a minimum. The two extreme solutions to this problem are: (i) Full communication: This essentially simulates the nondistributed setting to obtain the optimal O( log(n)T) regret bound at the cost of T communication.
Neural Information Processing Systems
Mar-14-2024, 03:10:21 GMT