Our Team
The aim of FairPlay is to develop and analyze algorithms that learn alongside users. Specifically, we focus on creating procedures capable of performing traditional learning tasks—such as prediction, decision-making, and explanation—when the data is generated or supplied by strategic agents or in the presence of competing learning agents. Our work emphasizes societal and ethical considerations, particularly regarding the fairness and privacy of the users involved.
Latest News
- Welcome, Gianmarco Genalti!We are excited to host Gianmarco Genalti, a visiting PhD student from Politecnico di Milano, from this week. His three…
- Two Papers Accepted to ICLR 2025!We are excited to announce that the papers “Feature-Based Online Bilateral Trade“ and “On Bits and Bandits: Quantifying the Regret-Information Trade-off“ have been accepted…
- Two Papers Accepted at AISTATS2025!We are pleased to announce that the papers “Distribution-Aware Mean Estimation under User-level Local Differential Privacy“ and “On Tradeoffs in Learning-Augmented Algorithms“ have been…
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