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Published online by Cambridge University Press: 20 July 2023
In practical applications, we typically solve the empirical risk minimization problem using optimization methods such as stochastic gradient descent (SGD). Such an algorithm searches a model parameter along a path that does not cover the entire model space. Therefore the empirical process analysis may not be optimal to analyze the performance of specific computational procedures. In recent years, another theoretical tool, which we may refer to as stability analysis, has been proposed to analyze such computational procedures.
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