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stat.ML2023
Bounded P-values in Parametric Programming-based Selective Inference
Tomohiro Shiraishi, Daiki Miwa, Vo Nguyen Le Duy +1
Selective inference (SI) has been actively studied as a promising framework for statistical hypothesis testing for data-driven hypotheses. The basic idea of SI is to make inference…
stat.ML2023
Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty
Yu Inatsu, Shion Takeno, Hiroyuki Hanada +2
In this study, we propose a novel multi-objective Bayesian optimization (MOBO) method to efficiently identify the Pareto front (PF) defined by risk measures for black-box functions…