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Sequential minimal optimization (SMO) is an algorithm for solving the quadratic programming (QP) problem that arises during the training of support-vector. Sequential model- based optimization (SMBO) iterates between fitting models and using them to make choices about which configurations to investigate. It offers. Sequential approximation techniques create a sequence of sub-problems that are easier to solve than the original problem. The approximate objective functions.