A receding-horizon estimation and control framework for the content sequencing problem. - Riccardo Busetto; Thomas Nakken Larsen; Adil Rasheed; Damiano Varagnolo; Simone Formentin (ECC, 2022)

META-SMGO-$ Delta$: Similarity as a Prior in Black-Box Optimization. - Riccardo Busetto; Valentina Breschi; Simone Formentin (CDC, 2023)

META-SMGO-Δ: similarity as a prior in black-box optimization. - Riccardo Busetto; Valentina Breschi; Simone Formentin (CoRR, 2023)

In-context learning of state estimators. - Riccardo Busetto; Valentina Breschi; Marco Forgione; Dario Piga; Simone Formentin (CoRR, 2023)

Hawkes-based cryptocurrency forecasting via Limit Order Book data. - Raffaele Giuseppe Cestari; Filippo Barchi; Riccardo Busetto; Daniele Marazzina; Simone Formentin (CoRR, 2023)

Meta-learning of data-driven controllers with automatic model reference tuning: theory and experimental case study. - Riccardo Busetto; Valentina Breschi; Federica Baracchi; Simone Formentin (CDC, 2024)

One controller to rule them all. - Riccardo Busetto; Valentina Breschi; Marco Forgione; Dario Piga; Simone Formentin (CoRR, 2024)

Meta-learning for model-reference data-driven control. - Riccardo Busetto; Valentina Breschi; Simone Formentin (Autom., 2025)

In-Context Learning for Zero-Shot Speed Estimation of BLDC motors. - Alessandro Colombo; Riccardo Busetto; Valentina Breschi; Marco Forgione; Dario Piga; Simone Formentin (CoRR, 2025)

Learning Low-Dimensional Embeddings for Black-Box Optimization. - Riccardo Busetto; Manas Mejari; Marco Forgione; Alberto Bemporad; Dario Piga (CoRR, 2025)