Pessimistic Rescaling and Distribution Shift of Boosting Models for Impression-Aware Online Advertising Recommendation. - Paolo Basso; Arturo Benedetti; Nicola Cecere; Alessandro Maranelli; Salvatore Marragony; Samuele Peri; Andrea Riboni; Alessandro Verosimile; Davide Zanutto; Maurizio Ferrari Dacrema (RecSys Challenge, 2023)

YoseUe: "trimming" Random Forest's training towards resource-constrained inference. - Alessandro Verosimile; Alessandro Tierno; Andrea Damiani; Marco D. Santambrogio (ASPDAC, 2024)

SATL: A Spatial Architecture Rapid Prototyping Framework for Irregular Applications Acceleration. - Francesco Peverelli; Alessandro Verosimile; Davide Conficconi; Andrea Damiani; Marco D. Santambrogio (ICCD, 2024)

Fast Voltage Estimation on MV Distribution Networks Through a Machine Learning Hybrid. - Leonardo Gori; Alessandro Verosimile; Andrea Damiani; Marco D. Santambrogio; Francesca Soldan; Enea Bionda; Carlo Tornelli (RTSI, 2024)

Moyogi: A Memory-Centric Accelerator for Low-Latency Random Forest Inference on Embedded Devices. - Alessandro Verosimile; Francesco Peverelli; Marco D. Santambrogio (FCCM, 2025)