Federico Cinus — accepted AI-conference papers

2026

Online Minimization of Polarization and Disagreement via Low-Rank Matrix Bandits

Federico Cinus, Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi

ICLR 2026poster

We study the problem of minimizing polarization and disagreement in the Friedkin–Johnsen opinion dynamics model under incomplete information. Unlike prior work that assumes a static setting with full knowledge of users' innate opinions, we address the more realistic online setting where innate opini…

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2025

Minimizing Polarization and Disagreement in the Friedkin–Johnsen Model with Unknown Innate Opinions

Federico Cinus, Atsushi Miyauchi, Yuko Kuroki, Francesco Bonchi

IJCAI 2025

The bulk of the literature on opinion optimization in social networks adopts the Friedkin–Johnsen (FJ) opinion dynamics model, in which the innate opinions of all nodes are known: this is an unrealistic assumption. In this paper, we study opinion optimization under the FJ model without the full know

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