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When the data is distributed across multiple servers, lowering the communication cost between the servers (or workers) while solving the distributed learning problem is an important problem and is the focus of this paper.
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The direct extension of admm for multi-block convex minimization problems is not necessarily convergent
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Angelia Nedić, Alex Olshevsky, and Michael G Rabbat · 2018
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Adaptive federated learning in resource constrained edge computing systems
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Asynchronous saddle point algorithm for stochastic optimization in heterogeneous networks
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