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StochaLM: a Stochastic alternate Linearization Method for distributed optimization
StochaLM can be interpreted as a dual block coordinate ascent method whose block components are selected using the state of an ergodic Markov chain.
DJAM: distributed Jacobi asynchronous method for learning personal models
We prove that DJAM converges with probability one to the solution, provided that the personal loss functions are strongly convex and have Lipschitz gradient.
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