Yoji Tomita — accepted AI-conference papers

2026

Beyond Match Maximization and Fairness: Retention-Optimized Two-Sided Matching

Ren Kishimoto, Rikiya Takehi, Koichi Tanaka, Yoji Tomita, Masahiro Nomura, Riku Togashi +1

ICLR 2026poster

On two-sided matching platforms such as online dating and recruiting, recommendation algorithms often aim to maximize the total number of matches. However, this objective creates an imbalance, where some users receive far too many matches while many others receive very few and eventually abandon the…

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2023

Daycare Matching in Japan: Transfers and Siblings

Zhaohong Sun, Yoshihiro Takenami, Daisuke Moriwaki, Yoji Tomita, Makoto Yokoo

AAAI 2023technical

In this paper, we study a daycare matching problem in Japan and report the design and implementation of a new centralized algorithm, which is going to be deployed in one municipality in the Tokyo metropolis. There are two features that make this market different from the classical hospital-doctor ma…

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