A novel graph-based model for hybrid recommendations in cold-start scenarios. - Cesare Bernardis; Maurizio Ferrari Dacrema; Paolo Cremonesi (CoRR, 2018)

Leveraging laziness, browsing-pattern aware stacked models for sequential accommodation learning to rank. - Edoardo D'Amico; Giovanni Gabbolini; Daniele Montesi; Matteo Moreschini; Federico Parroni; Federico Piccinini; Alberto Rossettini; Alessio Russo Introito; Cesare Bernardis; Maurizio Ferrari Dacrema (RecSys Challenge, 2019)

Estimating Confidence of Individual User Predictions in Item-based Recommender Systems. - Cesare Bernardis; Maurizio Ferrari Dacrema; Paolo Cremonesi (UMAP, 2019)

Multi-Objective Blended Ensemble For Highly Imbalanced Sequence Aware Tweet Engagement Prediction. - Nicolò Felicioni; Andrea Donati; Luca Conterio; Luca Bartoccioni; Davide Yi Xian Hu; Cesare Bernardis; Maurizio Ferrari Dacrema (RecSys Challenge, 2020)

Eigenvalue Perturbation for Item-based Recommender Systems. - Cesare Bernardis; Paolo Cremonesi (RecSys, 2021)

Lightweight and Scalable Model for Tweet Engagements Predictions in a Resource-constrained Environment. - Luca Carminati; Giacomo Lodigiani; Pietro Maldini; Samuele Meta; Stiven Metaj; Arcangelo Pisa; Alessandro Sanvito; Mattia Surricchio; Fernando Benjamín Pérez Maurera; Cesare Bernardis; Maurizio Ferrari Dacrema (RecSys Challenge, 2021)

On the instability of embeddings for recommender systems: the case of matrix factorization. - Giovanni Gabbolini; Edoardo D'Amico; Cesare Bernardis; Paolo Cremonesi (SAC, 2021)

On the impact of data sampling on hyper-parameter optimisation of recommendation algorithms. - Matteo Montanari; Cesare Bernardis; Paolo Cremonesi (SAC, 2022)

From Data Analysis to Intent-Based Recommendation: An Industrial Case Study in the Video Domain. - Cesare Bernardis; Maurizio Ferrari Dacrema; Fernando Benjamín Pérez Maurera; Massimo Quadrana; Mario Scriminaci; Paolo Cremonesi (IEEE Access, 2022)

Multi-stage Ensemble Model for Cross-market Recommendation. - Cesare Bernardis (CoRR, 2022)

Analyzing and improving stability of matrix factorization for recommender systems. - Edoardo D'Amico; Giovanni Gabbolini; Cesare Bernardis; Paolo Cremonesi (J. Intell. Inf. Syst., 2022)

NFC: a deep and hybrid item-based model for item cold-start recommendation. - Cesare Bernardis; Paolo Cremonesi (User Model. User Adapt. Interact., 2022)

On the effectiveness of neighborhood-based models in recommender systems - Cesare Bernardis (2022)