| 2026 | ACL | Losses that Cook: Topological Optimal Transport for Structured Recipe Generation. | Mattia Ottoborgo, Daniele Rege Cambrin, Paolo Garza |
| 2025 | CIKM | KIEPrompter: Leveraging Lightweight Models' Predictions for Cost-Effective Key Information Extraction using Vision LLMs. | Lorenzo Vaiani, Yihao Ding, Luca Cagliero, Jean Lee, Paolo Garza, Josiah Poon, Soyeon Caren Han |
| 2025 | CVPR | Turin3D: Evaluating Adaptation Strategies under Label Scarcity in Urban LiDAR Segmentation with Semi-Supervised Techniques. | Luca Barco, Giacomo Blanco, Gaetano Chiriaco, Alessia Intini, Luigi La Riccia, Vittorio Scolamiero, Piero Boccardo, Paolo Garza, Fabrizio Dominici |
| 2024 | ACL | 3MVRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understanding. | Yihao Ding, Lorenzo Vaiani, Soyeon Caren Han, Jean Lee, Paolo Garza, Josiah Poon, Luca Cagliero |
| 2024 | ECCV | Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height Estimation. | Daniele Rege Cambrin, Isaac Corley, Paolo Garza |
| 2024 | ECCV | Level Up Your Tutorials: VLMs for Game Tutorials Quality Assessment. | Daniele Rege Cambrin, Gabriele Scaffidi Militone, Luca Colomba, Giovanni Malnati, Daniele Apiletti, Paolo Garza |
| 2024 | ECCV | KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation. | Daniele Rege Cambrin, Eleonora Poeta, Eliana Pastor, Tania Cerquitelli, Elena Baralis, Paolo Garza |
| 2024 | ECIR | DQNC2S: DQN-Based Cross-Stream Crisis Event Summarizer. | Daniele Rege Cambrin, Luca Cagliero, Paolo Garza |
| 2024 | EMNLP | Beyond Accuracy Optimization: Computer Vision Losses for Large Language Model Fine-Tuning. | Daniele Rege Cambrin, Giuseppe Gallipoli, Irene Benedetto, Luca Cagliero, Paolo Garza |
| 2024 | ICASSP | Benchmarking Representations for Speech, Music, and Acoustic Events. | Moreno La Quatra, Alkis Koudounas, Lorenzo Vaiani, Elena Baralis, Luca Cagliero, Paolo Garza, Sabato Marco Siniscalchi |
| 2024 | ICLR | Paraphrase Loss for Abstractive Summarization. | Daniele Rege Cambrin, Paolo Garza |
| 2024 | ISCC | Throughput Prediction in Real-Time Communications: Spotlight on Traffic Extremes. | Tailai Song, Paolo Garza, Michela Meo, Maurizio Matteo Munaf |
| 2024 | ISM | Modelling Concurrent RTP Flows for End-to-end Predictions of QoS in Real Time Communications. | Tailai Song, Paolo Garza, Michela Meo, Maurizio Matteo Munaf |
| 2024 | LANMAN | Towards the Detection of Unobservable Losses in Real-Time Communications. | Tailai Song, Paolo Garza, Michela Meo, Maurizio Matteo Munaf |
| 2023 | ICDM | ViGEO: an Assessment of Vision GNNs in Earth Observation. | Luca Colomba, Paolo Garza |
| 2022 | CIKM | A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery. | Luca Colomba, Alessandro Farasin, Simone Monaco, Salvatore Greco, Paolo Garza, Daniele Apiletti, Elena Baralis, Tania Cerquitelli |
| 2022 | SAC | Leveraging multimodal content for podcast summarization. | Lorenzo Vaiani, Moreno La Quatra, Luca Cagliero, Paolo Garza |
| 2021 | EDBT | Double-Step deep learning framework to improve wildfire severity classification. | Simone Monaco, Andrea Pasini, Daniele Apiletti, Luca Colomba, Alessandro Farasin, Paolo Garza, Elena Baralis |
| 2021 | ICDE | DBSCOUT: A Density-based Method for Scalable Outlier Detection in Very Large Datasets. | Matteo Corain, Paolo Garza, Abolfazl Asudeh |
| 2020 | COMPSAC | DSLE: A Smart Platform for Designing Data Science Competitions. | Giuseppe Attanasio, Flavio Giobergia, Andrea Pasini, Francesco Ventura, Elena Baralis, Luca Cagliero, Paolo Garza, Daniele Apiletti, Tania Cerquitelli, Silvia Chiusano |
| 2020 | EDBT | Cross-Lingual Propagation of Sentiment Information Based on Bilingual Vector Space Alignment. | Flavio Giobergia, Luca Cagliero, Paolo Garza, Elena Baralis |
| 2020 | KES | An explainable data-driven approach to web directory taxonomy mapping. | Elena Daraio, Luca Cagliero, Silvia Chiusano, Paolo Garza, Giuseppe Ricupero |
| 2020 | SIGMOD | Price series cross-correlation analysis to enhance the diversification of itemset-based stock portfolios. | Jacopo Fior, Luca Cagliero, Paolo Garza |
| 2019 | BigData | CarPredictor: Forecasting the Number of Free Floating Car Sharing Vehicles within Restricted Urban Areas. | Luca Cagliero, Silvia Chiusano, Elena Daraio, Paolo Garza |
| 2019 | EDBT | Adaptive Hierarchical Clustering for Petrographic Image Analysis. | Andrea Pasini, Elena Baralis, Paolo Garza, Davide Floriello, Michela Idiomi, Andrea Ortenzi, Simone Ricci |
| 2019 | ICDM | Combining News Sentiment and Technical Analysis to Predict Stock Trend Reversal. | Giuseppe Attanasio, Luca Cagliero, Paolo Garza, Elena Baralis |
| 2019 | SIGMOD | Quantitative cryptocurrency trading: exploring the use of machine learning techniques. | Giuseppe Attanasio, Luca Cagliero, Paolo Garza, Elena Baralis |
| 2018 | EDBT | Study of the Applicability of an Itemset-Based Portfolio Planner in a Multi-Market Context. | Luca Cagliero, Paolo Garza |
| 2017 | ADBIS | Discovering High-Utility Itemsets at Multiple Abstraction Levels. | Luca Cagliero, Silvia Chiusano, Paolo Garza, Giuseppe Ricupero |
| 2017 | SIGIR | Identifying Collaborations among Researchers: a pattern-based approach. | Luca Cagliero, Paolo Garza, Mohammad Reza Kavoosifar, Elena Baralis |
| 2016 | ADBIS | Reducing Big Data by Means of Context-Aware Tailoring. | Paolo Garza, Elisa Quintarelli, Emanuele Rabosio, Letizia Tanca |
| 2016 | ADBIS | BAC: A Bagged Associative Classifier for Big Data Frameworks. | Luca Venturini, Paolo Garza, Daniele Apiletti |
| 2016 | NOMS | SaFe-NeC: A scalable and flexible system for network data characterization. | Daniele Apiletti, Elena Baralis, Tania Cerquitelli, Paolo Garza, Luca Venturini |
| 2016 | SmartComp | Modeling Correlations among Air Pollution-Related Data through Generalized Association Rules. | Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Paolo Garza, Giuseppe Ricupero, Xin Xiao |
| 2015 | ADBIS | A Review of Scalable Approaches for Frequent Itemset Mining. | Daniele Apiletti, Paolo Garza, Fabio Pulvirenti |
| 2015 | BigData | PaWI: Parallel Weighted Itemset Mining by Means of MapReduce. | Elena Baralis, Luca Cagliero, Paolo Garza, Luigi Grimaudo |
| 2015 | ICDM | PaMPa-HD: A Parallel MapReduce-Based Frequent Pattern Miner for High-Dimensional Data. | Daniele Apiletti, Elena Baralis, Tania Cerquitelli, Paolo Garza, Pietro Michiardi, Fabio Pulvirenti |
| 2014 | ISPA | Misleading Generalized Itemset Mining in the Cloud. | Elena Baralis, Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Paolo Garza, Luigi Grimaudo, Fabio Pulvirenti |
| 2014 | UCC | NEMICO: Mining Network Data through Cloud-Based Data Mining Techniques. | Elena Baralis, Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Paolo Garza, Luigi Grimaudo, Fabio Pulvirenti |
| 2013 | ADBIS | Hadoop on a Low-Budget General Purpose HPC Cluster in Academia. | Paolo Garza, Paolo Margara, Nicol Nepote, Luigi Grimaudo, Elio Piccolo |
| 2013 | BIBE | Frequent weighted itemset mining from gene expression data. | Elena Baralis, Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Paolo Garza |
| 2011 | CIKM | Structured data classification by means of matrix factorization. | Paolo Garza |
| 2009 | KES | Context-Aware User and Service Profiling by Means of Generalized Association Rules. | Elena Baralis, Luca Cagliero, Tania Cerquitelli, Paolo Garza, Marco Marchetti |
| 2006 | SAC | Associative text categorization exploiting negated words. | Elena Baralis, Paolo Garza |
| 2004 | SAC | On support thresholds in associative classification. | Elena Baralis, Silvia Chiusano, Paolo Garza |
| 2002 | ICDM | A Lazy Approach to Pruning Classification Rules. | Elena Baralis, Paolo Garza |