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Solving Constrained CASH Problems with ADMM
Published 17 Jun 2020 in cs.LG, math.OC, and stat.ML | (2006.09635v2)
Abstract: The CASH problem has been widely studied in the context of automated configurations of ML pipelines and various solvers and toolkits are available. However, CASH solvers do not directly handle black-box constraints such as fairness, robustness or other domain-specific custom constraints. We present our recent approach [Liu, et al., 2020] that leverages the ADMM optimization framework to decompose CASH into multiple small problems and demonstrate how ADMM facilitates incorporation of black-box constraints.
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