Maurizio Ferrari Dacrema

98 papers A* 6A 9C 2Misc 4Journal 39Unranked 34
YearRankTypeTitle / Venue / Authors
2026 J jnl
Diffusion Recommender Models and the Illusion of Progress: A Concerning Study of Reproducibility and a Conceptual Mismatch.
Trans. Recomm. Syst.
Michael Benigni, Maurizio Ferrari Dacrema, Dietmar Jannach
2026 J jnl
Minor embedding for quantum annealing with reinforcement learning.
Quantum Mach. Intell.
Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2026 — conf
QuantumCLEF 2026 The Third Edition of the Quantum Computing Lab at CLEF.
ECIR (4)
Andrea Pasin, Maurizio Ferrari Dacrema, Paolo Cremonesi, Washington Cunha, Marcos André Gonçalves, Nicola Ferro
2026 J jnl
Reproducibility and Artifact Consistency of the SIGIR 2022 Recommender Systems Papers Based on Message Passing.
ACM Trans. Inf. Syst.
Maurizio Ferrari Dacrema, Michael Benigni, Nicola Ferro
2025 A conf
A Hands-on Dive Into Quantum Computing for Recommender Systems.
RecSys
Maurizio Ferrari Dacrema, Paolo Cremonesi
2025 A* conf
A Worrying Reproducibility Study of Intent-Aware Recommendation Models.
SIGIR
Faisal Shehzad, Maurizio Ferrari Dacrema, Dietmar Jannach
2025 J jnl
A Worrying Reproducibility Study of Intent-Aware Recommendation Models.
CoRR
Faisal Shehzad, Maurizio Ferrari Dacrema, Dietmar Jannach
2025 J jnl
Automated Design of Structured Variational Quantum Circuits with Reinforcement Learning.
CoRR
Gloria Turati, Simone Foderà, Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2025 — conf
Diffusion Models for Recommendation: Reproducibility and Conceptual Mismatch.
IIR
Michael Benigni, Maurizio Ferrari Dacrema, Dietmar Jannach
2025 J jnl
Diffusion Recommender Models and the Illusion of Progress: A Concerning Study of Reproducibility and a Conceptual Mismatch.
CoRR
Michael Benigni, Maurizio Ferrari Dacrema, Dietmar Jannach
2025 J jnl
Hamiltonian Expressibility for Ansatz Selection in Variational Quantum Algorithms.
CoRR
Filippo Brozzi, Gloria Turati, Maurizio Ferrari Dacrema, Filippo Caruso, Paolo Cremonesi
2025 J jnl
Impression-Aware Recommender Systems.
Trans. Recomm. Syst.
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Pablo Castells, Paolo Cremonesi
2025 J jnl
Minor Embedding for Quantum Annealing with Reinforcement Learning.
CoRR
Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2025 — conf
Overview of QuantumCLEF 2025: The Second Quantum Computing Challenge for Information Retrieval and Recommender Systems at CLEF.
CLEF
Andrea Pasin, Maurizio Ferrari Dacrema, Washington Cunha, Marcos André Gonçalves, Paolo Cremonesi, Nicola Ferro
2025 — conf
QAOA for Efficient Urban Logistical Ecosystem.
AIQxQIA@ECAI
Fabio Picariello, Gloria Turati, Riccardo Antonelli, Igor Bailo, Susanna Bonura, Gianmarco Ciarfaglia, Salvatore Cipolla, Paolo Cremonesi, Maurizio Ferrari Dacrema, Michele Gabusi, Ivan Gentile, Vito Morreale, Antonio Noto
2025 J jnl
Quantum Approaches to Urban Logistics: From Core QAOA to Clustered Scalability.
CoRR
Fabio Picariello, Gloria Turati, Riccardo Antonelli, Igor Bailo, Susanna Bonura, Gianmarco Ciarfaglia, Salvatore Cipolla, Paolo Cremonesi, Maurizio Ferrari Dacrema, Michele Gabusi, Ivan Gentile, Vito Morreale, Antonio Noto
2025 — conf
QuantumCLEF 2025 - The Second Edition of the Quantum Computing Lab at CLEF.
ECIR (5)
Andrea Pasin, Maurizio Ferrari Dacrema, Paolo Cremonesi, Washington Cunha, Marcos André Gonçalves, Nicola Ferro
2025 — conf
QuantumCLEF 2025: Overview of the Second Quantum Computing Challenge for Information Retrieval and Recommender Systems at CLEF.
CLEF (Working Notes)
Andrea Pasin, Maurizio Ferrari Dacrema, Washington Cunha, Marcos André Gonçalves, Paolo Cremonesi, Nicola Ferro
2025 J jnl
Reproducibility and Artifact Consistency of the SIGIR 2022 Recommender Systems Papers Based on Message Passing.
CoRR
Maurizio Ferrari Dacrema, Michael Benigni, Nicola Ferro
2024 Misc conf
Adaptive Learning for Quantum Linear Regression.
QCE
Costantino Carugno, Maurizio Ferrari Dacrema, Paolo Cremonesi
2024 J jnl
Adaptive Learning for Quantum Linear Regression.
CoRR
Costantino Carugno, Maurizio Ferrari Dacrema, Paolo Cremonesi
2024 — conf
An Application of Reinforcement Learning for Minor Embedding in Quantum Annealing (Short Paper).
AIQxQIA@AI*IA
Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2024 J jnl
Analyzing the Effectiveness of Quantum Annealing with Meta-Learning.
CoRR
Riccardo Pellini, Maurizio Ferrari Dacrema
2024 J jnl
Analyzing the effectiveness of quantum annealing with meta-learning.
Quantum Mach. Intell.
Riccardo Pellini, Maurizio Ferrari Dacrema
2024 J jnl
AutoOPE: Automated Off-Policy Estimator Selection.
CoRR
Nicolò Felicioni, Michael Benigni, Maurizio Ferrari Dacrema
2024 — conf
Exploiting Contextual Normalizations and Article Endorsement for News Recommendation.
RecSys Challenge
Andrea Alari, Lorenzo Campana, Federico Giuseppe Ciliberto, Saverio Maggese, Carlo Sgaravatti, Francesco Zanella, Andrea Pisani, Maurizio Ferrari Dacrema
2024 — conf
Leveraging Semantic Embeddings of User Reviews with Off-the-Shelf LLMs for Recommender Systems.
IIR
Nicola Cecere, Andrea Pisani, Maurizio Ferrari Dacrema, Paolo Cremonesi
2024 — conf
Overview of QuantumCLEF 2024: The Quantum Computing Challenge for Information Retrieval and Recommender Systems at CLEF.
CLEF (2)
Andrea Pasin, Maurizio Ferrari Dacrema, Paolo Cremonesi, Nicola Ferro
2024 — conf
Pre-Trained LLM Embeddings of Product Reviews for Recommendation.
IIR
Andrea Pisani, Nicola Cecere, Maurizio Ferrari Dacrema, Paolo Cremonesi
2024 — conf
Quantum Computing for Information Retrieval and Recommender Systems.
ECIR (5)
Maurizio Ferrari Dacrema, Andrea Pasin, Paolo Cremonesi, Nicola Ferro
2024 — conf
QuantumCLEF - Quantum Computing at CLEF.
ECIR (5)
Andrea Pasin, Maurizio Ferrari Dacrema, Paolo Cremonesi, Nicola Ferro
2024 — conf
QuantumCLEF 2024: Overview of the Quantum Computing Challenge for Information Retrieval and Recommender Systems at CLEF.
CLEF (Working Notes)
Andrea Pasin, Maurizio Ferrari Dacrema, Paolo Cremonesi, Nicola Ferro
2024 — conf
Reinforcement Learning for Variational Quantum Circuit Design.
AIQxQIA@AI*IA
Simone Foderà, Gloria Turati, Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2024 J jnl
Reinforcement Learning for Variational Quantum Circuits Design.
CoRR
Simone Foderà, Gloria Turati, Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2024 A* conf
Using and Evaluating Quantum Computing for Information Retrieval and Recommender Systems.
SIGIR
Maurizio Ferrari Dacrema, Andrea Pasin, Paolo Cremonesi, Nicola Ferro
2023 Misc conf
Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances.
QCE
Gloria Turati, Maurizio Ferrari Dacrema, Paolo Cremonesi
2023 J jnl
Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances.
CoRR
Gloria Turati, Maurizio Ferrari Dacrema, Paolo Cremonesi
2023 — conf
Characterizing Impression-Aware Recommender Systems.
LERI@RecSys
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Pablo Castells, Paolo Cremonesi
2023 J jnl
Impression-Aware Recommender Systems.
CoRR
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Pablo Castells, Paolo Cremonesi
2023 — conf
Impressions in Recommender Systems: Present and Future.
IIR
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Pablo Castells, Paolo Cremonesi
2023 — conf
Incorporating Impressions to Graph-Based Recommenders.
LERI@RecSys
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Pablo Castells, Paolo Cremonesi
2023 — conf
Pessimistic Rescaling and Distribution Shift of Boosting Models for Impression-Aware Online Advertising Recommendation.
RecSys Challenge
Paolo Basso, Arturo Benedetti, Nicola Cecere, Alessandro Maranelli, Salvatore Marragony, Samuele Peri, Andrea Riboni, Alessandro Verosimile, Davide Zanutto, Maurizio Ferrari Dacrema
2023 — ed.
Proceedings of the Workshop on Learning and Evaluating Recommendations with Impressions co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 19th, 2023.
LERI@RecSys
Maurizio Ferrari Dacrema, Pablo Castells, Justin Basilico, Paolo Cremonesi
2023 J jnl
Report on the Workshop on Learning and Evaluating Recommendations with Impressions (LERI) at RecSys 2023.
SIGIR Forum
Maurizio Ferrari Dacrema, Pablo Castells, Justin Basilico, Paolo Cremonesi
2023 — conf
Towards Improved QUBO Formulations of IR Tasks for Quantum Annealers.
IIR
Riccardo Pellini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2023 A conf
Workshop on Learning and Evaluating Recommendations with Impressions (LERI).
RecSys
Maurizio Ferrari Dacrema, Pablo Castells, Justin Basilico, Paolo Cremonesi
2023 — conf
qCLEF: A Proposal to Evaluate Quantum Annealing for Information Retrieval and Recommender Systems.
CLEF
Andrea Pasin, Maurizio Ferrari Dacrema, Paolo Cremonesi, Nicola Ferro
2022 — conf
An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering.
ECIR (1)
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi
2022 J jnl
An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering.
CoRR
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi
2022 — ch.
Design and Evaluation of Cross-Domain Recommender Systems.
Recommender Systems Handbook
Maurizio Ferrari Dacrema, Iván Cantador, Ignacio Fernández-Tobías, Shlomo Berkovsky, Paolo Cremonesi
2022 — conf
Evaluating Recommendations in a User Interface With Multiple Carousels.
IIR
Maurizio Ferrari Dacrema, Nicolò Felicioni, Paolo Cremonesi
2022 Misc conf
Feature Selection for Classification with QAOA.
QCE
Gloria Turati, Maurizio Ferrari Dacrema, Paolo Cremonesi
2022 J jnl
Feature Selection for Classification with QAOA.
CoRR
Gloria Turati, Maurizio Ferrari Dacrema, Paolo Cremonesi
2022 — conf
Feature Selection via Quantum Annealers for Ranking and Classification Tasks.
IIR
Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro, Guglielmo Faggioli, Paolo Cremonesi
2022 J jnl
From Data Analysis to Intent-Based Recommendation: An Industrial Case Study in the Video Domain.
IEEE Access
Cesare Bernardis, Maurizio Ferrari Dacrema, Fernando Benjamín Pérez Maurera, Massimo Quadrana, Mario Scriminaci, Paolo Cremonesi
2022 A* conf
Off-Policy Evaluation with Deficient Support Using Side Information.
NeurIPS
Nicolò Felicioni, Maurizio Ferrari Dacrema, Marcello Restelli, Paolo Cremonesi
2022 J jnl
Offline Evaluation of Recommender Systems in a User Interface With Multiple Carousels.
Frontiers Big Data
Maurizio Ferrari Dacrema, Nicolò Felicioni, Paolo Cremonesi
2022 — conf
Replication of Collaborative Filtering Generative Adversarial Networks on Recommender Systems.
IIR
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi
2022 — conf
Replication of Recommender Systems with Impressions.
IIR
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi
2022 A* conf
Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers.
SIGIR
Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro, Guglielmo Faggioli, Paolo Cremonesi
2022 J jnl
Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers.
CoRR
Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro, Guglielmo Faggioli, Paolo Cremonesi
2022 A conf
Towards Recommender Systems with Community Detection and Quantum Computing.
RecSys
Riccardo Nembrini, Costantino Carugno, Maurizio Ferrari Dacrema, Paolo Cremonesi
2022 A conf
Towards the Evaluation of Recommender Systems with Impressions.
RecSys
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi
2022 Misc conf
Virtual Network Function Embedding with Quantum Annealing.
QCE
Pietro Chiavassa, Andrea Marchesin, Ignazio Pedone, Maurizio Ferrari Dacrema, Paolo Cremonesi
2021 — conf
A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels.
UMAP (Adjunct Publication)
Nicolò Felicioni, Maurizio Ferrari Dacrema, Paolo Cremonesi
2021 J jnl
A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels.
CoRR
Nicolò Felicioni, Maurizio Ferrari Dacrema, Paolo Cremonesi
2021 J jnl
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research.
ACM Trans. Inf. Syst.
Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi, Dietmar Jannach
2021 A* conf
Demonstrating the Equivalence of List Based and Aggregate Metrics to Measure the Diversity of Recommendations (Student Abstract).
AAAI
Maurizio Ferrari Dacrema
2021 J jnl
Feature Selection for Recommender Systems with Quantum Computing.
CoRR
Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2021 J jnl
Feature Selection for Recommender Systems with Quantum Computing.
Entropy
Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
2021 — conf
Lightweight and Scalable Model for Tweet Engagements Predictions in a Resource-constrained Environment.
RecSys Challenge
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
2021 — conf
Measuring the Ranking Quality of Recommendations in a Two-Dimensional Carousel Setting.
IIR
Nicolò Felicioni, Maurizio Ferrari Dacrema, Fernando Benjamín Pérez Maurera, Paolo Cremonesi
2021 C conf
Measuring the User Satisfaction in a Recommendation Interface with Multiple Carousels.
IMX
Nicolò Felicioni, Maurizio Ferrari Dacrema, Paolo Cremonesi
2021 J jnl
Measuring the User Satisfaction in a Recommendation Interface with Multiple Carousels.
CoRR
Nicolò Felicioni, Maurizio Ferrari Dacrema, Paolo Cremonesi
2021 A conf
Optimizing the Selection of Recommendation Carousels with Quantum Computing.
RecSys
Maurizio Ferrari Dacrema, Nicolò Felicioni, Paolo Cremonesi
2020 — —
An assessment of reproducibility and methodological issues in neural recommender systems research.
Maurizio Ferrari Dacrema
2020 J jnl
Artist-driven layering and user's behaviour impact on recommendations in a playlist continuation scenario.
CoRR
Sebastiano Antenucci, Simone Boglio, Emanuele Chioso, Ervin Dervishaj, Shuwen Kang, Tommaso Scarlatti, Maurizio Ferrari Dacrema
2020 A conf
ContentWise Impressions: An Industrial Dataset with Impressions Included.
CIKM
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Lorenzo Saule, Mario Scriminaci, Paolo Cremonesi
2020 J jnl
ContentWise Impressions: An industrial dataset with impressions included.
CoRR
Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Lorenzo Saule, Mario Scriminaci, Paolo Cremonesi
2020 A conf
Critically Examining the Claimed Value of Convolutions over User-Item Embedding Maps for Recommender Systems.
CIKM
Maurizio Ferrari Dacrema, Federico Parroni, Paolo Cremonesi, Dietmar Jannach
2020 J jnl
Critically Examining the Claimed Value of Convolutions over User-Item Embedding Maps for Recommender Systems.
CoRR
Maurizio Ferrari Dacrema, Federico Parroni, Paolo Cremonesi, Dietmar Jannach
2020 A* conf
Methodological Issues in Recommender Systems Research (Extended Abstract).
IJCAI
Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach
2020 — conf
Multi-Objective Blended Ensemble For Highly Imbalanced Sequence Aware Tweet Engagement Prediction.
RecSys Challenge
Nicolò Felicioni, Andrea Donati, Luca Conterio, Luca Bartoccioni, Davide Yi Xian Hu, Cesare Bernardis, Maurizio Ferrari Dacrema
2019 J jnl
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research.
CoRR
Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi, Dietmar Jannach
2019 J jnl
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches.
CoRR
Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach
2019 A conf
Are we really making much progress? A worrying analysis of recent neural recommendation approaches.
RecSys
Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach
2019 A conf
Estimating Confidence of Individual User Predictions in Item-based Recommender Systems.
UMAP
Cesare Bernardis, Maurizio Ferrari Dacrema, Paolo Cremonesi
2019 — conf
Leveraging laziness, browsing-pattern aware stacked models for sequential accommodation learning to rank.
RecSys Challenge
Edoardo D'Amico, Giovanni Gabbolini, Daniele Montesi, Matteo Moreschini, Federico Parroni, Federico Piccinini, Alberto Rossettini, Alessio Russo Introito, Cesare Bernardis, Maurizio Ferrari Dacrema
2019 J jnl
Movie genome: alleviating new item cold start in movie recommendation.
User Model. User Adapt. Interact.
Yashar Deldjoo, Maurizio Ferrari Dacrema, Mihai Gabriel Constantin, Hamid Eghbal-zadeh, Stefano Cereda, Markus Schedl, Bogdan Ionescu, Paolo Cremonesi
2019 — conf
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features.
IntRS@RecSys
Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema, Markus Schedl, Paolo Cremonesi
2019 J jnl
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features.
CoRR
Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema, Markus Schedl, Paolo Cremonesi
2018 J jnl
A novel graph-based model for hybrid recommendations in cold-start scenarios.
CoRR
Cesare Bernardis, Maurizio Ferrari Dacrema, Paolo Cremonesi
2018 C conf
Aggregating Models for Anomaly Detection in Space Systems: Results from the FCTMAS Study.
IAS
Francesco Amigoni, Maurizio Ferrari Dacrema, Alessandro Donati, Christian Laroque, Michèle Lavagna, Alessandro Riva
2018 — conf
Artist-driven layering and user's behaviour impact on recommendations in a playlist continuation scenario.
RecSys Challenge
Sebastiano Antenucci, Simone Boglio, Emanuele Chioso, Ervin Dervishaj, Shuwen Kang, Tommaso Scarlatti, Maurizio Ferrari Dacrema
2018 — conf
Deriving Item Features Relevance from Collaborative Domain Knowledge.
KaRS@RecSys
Maurizio Ferrari Dacrema, Alberto Gasparin, Paolo Cremonesi
2018 J jnl
Deriving item features relevance from collaborative domain knowledge.
CoRR
Maurizio Ferrari Dacrema, Alberto Gasparin, Paolo Cremonesi
2018 J jnl
Eigenvalue analogy for confidence estimation in item-based recommender systems.
CoRR
Maurizio Ferrari Dacrema, Paolo Cremonesi
2018 — ch.
User Preference Sources: Explicit vs. Implicit Feedback.
Collaborative Recommendations
Paolo Cremonesi, Franca Garzotto, Maurizio Ferrari Dacrema