arXiv (OAI Expanded)
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Finite-sample guarantees for data-driven operator splitting methods via martingale inequalities
Operator splitting methods are a fundamental class of algorithms for solving structured monotone inclusion problems arising in optimization, control, and game theory. We consider the case, common in stochastic regimes, where the forward evaluation of one of the constituent operators is either unavai
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