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Adaptive Consensus: A network pruning approach for decentralized optimization
We consider network-based decentralized optimization problems, where each node in the network possesses a local function and the objective is to collectively attain a consensus solution that minimizes the sum of all the local functions.
Dynamic social learning under graph constraints
We introduce a model of graph-constrained dynamic choice with reinforcement modeled by positively $\alpha$-homogeneous rewards.
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