| 2026 | COLT | Learning Conditional Averages. | Marco Bressan, Nataly Brukhim, Nicol Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen |
| 2026 | COLT | Active Learning on Adversarially Corrupted Graphs. | Marco Bressan, Nicol Cesa-Bianchi, Tommaso d'Orsi, Emmanuel Esposito, Silvio Lattanzi |
| 2026 | SODA | The Parameterised Complexity of Counting Small Sub-Hypergraphs. | Marco Bressan, Julian Christoph Brinkmann, Holger Dell, Marc Roth, Philip Wellnitz |
| 2025 | COLT | Of Dice and Games: A Theory of Generalized Boosting. | Marco Bressan, Nataly Brukhim, Nicol Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen |
| 2025 | COLT | A Fine-grained Characterization of PAC Learnability. | Marco Bressan, Nataly Brukhim, Nicol Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen |
| 2024 | COLT | A Theory of Interpretable Approximations. | Marco Bressan, Nicol Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen |
| 2024 | COLT | Efficient Algorithms for Learning Monophonic Halfspaces in Graphs. | Marco Bressan, Emmanuel Esposito, Maximilian Thiessen |
| 2024 | ICML | Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees. | Marco Bressan, Mauro Sozio |
| 2023 | AAAI | Fully-Dynamic Decision Trees. | Marco Bressan, Gabriel Damay, Mauro Sozio |
| 2023 | STOC | The Complexity of Pattern Counting in Directed Graphs, Parameterised by the Outdegree. | Marco Bressan, Matthias Lanzinger, Marc Roth |
| 2021 | COLT | Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries. | Marco Bressan, Nicol Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice |
| 2021 | FOCS | Exact and Approximate Pattern Counting in Degenerate Graphs: New Algorithms, Hardness Results, and Complexity Dichotomies. | Marco Bressan, Marc Roth |
| 2021 | STOC | Efficient and near-optimal algorithms for sampling connected subgraphs. | Marco Bressan |
| 2018 | FOCS | Sublinear Algorithms for Local Graph Centrality Estimation. | Marco Bressan, Enoch Peserico, Luca Pretto |
| 2018 | STACS | On Approximating the Stationary Distribution of Time-reversible Markov Chains. | Marco Bressan, Enoch Peserico, Luca Pretto |
| 2018 | SPAA | Brief Announcement: On Approximating PageRank Locally with Sublinear Query Complexity. | Marco Bressan, Enoch Peserico, Luca Pretto |
| 2017 | WSDM | Counting Graphlets: Space vs Time. | Marco Bressan, Flavio Chierichetti, Ravi Kumar, Stefano Leucci, Alessandro Panconesi |
| 2016 | KDD | The Limits of Popularity-Based Recommendations, and the Role of Social Ties. | Marco Bressan, Stefano Leucci, Alessandro Panconesi, Prabhakar Raghavan, Erisa Terolli |
| 2013 | WWW | The power of local information in PageRank. | Marco Bressan, Enoch Peserico, Luca Pretto |
| 2011 | CIKM | Local computation of PageRank: the ranking side. | Marco Bressan, Luca Pretto |
| 2011 | CLUSTER | Datamation: A Quarter of a Century and Four Orders of Magnitude Later. | Paolo Bertasi, Michele Bonazza, Marco Bressan, Enoch Peserico |
| 2010 | FUN | Urban Hitchhiking. | Marco Bressan, Enoch Peserico |
| 2009 | WAW | Choose the Damping, Choose the Ranking?. | Marco Bressan, Enoch Peserico |
| 2008 | ICIP | An analysis of the relationship between painters based on their work. | Marco Bressan, Claudio Cifarelli, Florent Perronnin |
| 2006 | ECCV | Adapted Vocabularies for Generic Visual Categorization. | Florent Perronnin, Christopher R. Dance, Gabriela Csurka, Marco Bressan |
| 2001 | CVPR | Using an ICA Representation of High Dimensional Data for Object Recognition and Classification. | Marco Bressan, David Guillamet, Jordi Vitri |
| 2001 | CVPR | A Weighted Non-Negative Matrix Factorization for Local Representations. | David Guillamet, Marco Bressan, Jordi Vitri |