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NeurIPS 2026RIKEN AIP The UnivThe University of Osaka / RIKEN Learning theory

Information-Theoretic Generalization for Set-Input Optimization-Valued Objectives

Futoshi Futami, Masahiro Fujisawa

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026RIKEN AIP The UnivThe University of Osaka / RIKEN Learning theory

Information-Theoretic Generalization Bounds for Sequential Decision Making

A sequential supersample framework bounds sequential decision-making generalization via roundwise mutual information and faster Bernstein rates, applying to online learning and bandits.

Futoshi Futami, Masahiro Fujisawa

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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