33 citations · 42 across the 16 of their papers we have counts for
4 papers · 2 filters
Information-Theoretic Generalization for Set-Input Optimization-Valued Objectives
Futoshi Futami, Masahiro Fujisawa
Modern machine learning is increasingly evaluated using criteria such as multicalibration, CVaR, and Cressie-Read DRO, which target subgroup reliability, tail risk, and distributio…
Hierarchical Utility Calibration for Structured Multiclass Decisions
Futoshi Futami, Jerry Huang, Ichiro Takeuchi
In multiclass probabilistic prediction, Utility Calibration (UC), which focuses auditing on specified utilities, has recently received attention as a way to guarantee downstream de…
Information-Theoretic Generalization Bounds for Sequential Decision Making
Futoshi Futami, Masahiro Fujisawa
Information-theoretic generalization bounds based on the supersample construction are a central tool for algorithm-dependent generalization analysis in the batch i.i.d. setting. Ho…
Unified Approach for Weakly Supervised Multicalibration
Futoshi Futami, Takashi Ishida
Multicalibration requires predicted scores to agree with label probabilities across rich families of subgroups and score-dependent tests, but existing methods require clean input-l…