استفاده از معیارهای ریسک مالی برای تجزیه و تحلیل عملکرد تعمیم مدل های یادگیری ماشین

In this paper, after relating existing learning models to UMLM, we show some theoretical properties for UMLM. Concretely, we show an interpretation of UMLM as minimizing a well-known financial risk measure (worst-case value-at risk (VaR) or conditional VaR), derive generalization bounds for UMLM using such a risk measure, and prove that solving problems of UMLM leads to estimators with the minimized generalization bounds. Those theoretical properties are applicable to related existing learning models.