Mattia Cerrato

37 papers A* 3B 5C 1Misc 1Journal 18Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Rashomon Sets and Model Multiplicity in Federated Learning. CoRR Xenia Heilmann, Luca Corbucci, Mattia Cerrato
2026	J	`jnl`	Science-Gym: a simple testbed for AI-driven scientific discovery. Mach. Learn. Mattia Cerrato, Lennart Baur, Jannis Brugger, Sajjad Shumaly, Nicholas Schmitt, Edward Finkelstein, Selina Jukic, Lars Münzel, Felix Peter Paul, Pascal Pfannes, Benedikt Rohr, Julius Schellenberg, Philipp Wolf, Stefan Kramer
2025	—	`conf`	A Benchmark for Client-level Fairness in Federated Learning. EWAF Xenia Heilmann, Luca Corbucci, Mattia Cerrato
2025	C	`conf`	A Neurosymbolic Approach to Counterfactual Fairness. NeSy Xenia Heilmann, Chiara Manganini, Mattia Cerrato, Vaishak Belle
2025	—	`conf`	Benefits of the Federation? Analyzing the Impact of Fair Federated Learning at the Client Level. FAccT Luca Corbucci, Xenia Heilmann, Mattia Cerrato
2025	B	`conf`	Exploring the Design Space of Fair Tree Learning Algorithms. DS Kiara Stempel, Mattia Cerrato, Stefan Kramer
2025	J	`jnl`	Exploring the Design Space of Fair Tree Learning Algorithms. CoRR Kiara Stempel, Mattia Cerrato, Stefan Kramer
2025	J	`jnl`	FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation. CoRR Xenia Heilmann, Luca Corbucci, Mattia Cerrato, Anna Monreale
2025	J	`jnl`	N-Parties Private Structure and Parameter Learning for Sum-Product Networks. CoRR Xenia Heilmann, Ernst Althaus, Mattia Cerrato, Nick Johannes Peter Rassau, Mohammad Sadeq Dousti, Stefan Kramer
2025	J	`jnl`	Neural-Guided Equation Discovery. CoRR Jannis Brugger, Mattia Cerrato, David Richter, Cedric Derstroff, Daniel Maninger, Mira Mezini, Stefan Kramer
2025	—	`ed.`	Proceedings of the 3rd European Workshop on Algorithmic Fairness, Mainz, Germany, July 1st to 3rd, 2024. EWAF Mattia Cerrato, Alesia Vallenas Coronel, Petra Ahrweiler, Michele Loi, Mykola Pechenizkiy, Aurelia Tamò-Larrieux
2025	—	`conf`	Stochastic Fairness Interventions Are Arbitrary. EWAF Mattia Cerrato, Marius Köppel, Kiara Stempel, Philipp Wolf, Stefan Kramer
2024	J	`jnl`	10 Years of Fair Representations: Challenges and Opportunities. CoRR Mattia Cerrato, Marius Köppel, Philipp Wolf, Stefan Kramer
2024	A*	`conf`	Differentially Private Sum-Product Networks. ICML Xenia Heilmann, Mattia Cerrato, Ernst Althaus
2024	J	`jnl`	Partitioned least squares. Mach. Learn. Roberto Esposito, Mattia Cerrato, Marco Locatelli
2024	A*	`conf`	Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. AAAI Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer
2024	J	`jnl`	Predicting NOx emissions in Biochar Production Plants using Machine Learning. CoRR Marius Köppel, Niklas Witzig, Tim Klausmann, Mattia Cerrato, Tobias Schweitzer, Jochen Weber, Erdem Yilmaz, Juan Chimbo, Bernardo del Campo, Lissete Davila, David Barreno
2024	—	`conf`	Science-Gym: A Simple Testbed for AI-Driven Scientific Discovery. DS (1) Mattia Cerrato, Nicholas Schmitt, Lennart Baur, Edward Finkelstein, Selina Jukic, Lars Münzel, Felix Peter Paul, Pascal Pfannes, Benedikt Rohr, Julius Schellenberg, Philipp Wolf, Stefan Kramer
2024	—	`conf`	Trust in Fair Algorithms: Pilot Experiment. EWAF Mattia Cerrato, Marius Köppel, Kiara Stempel, Alesia Vallenas Coronel, Niklas Witzig
2023	J	`jnl`	Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. CoRR Stefan Kramer, Mattia Cerrato, Saso Dzeroski, Ross D. King
2023	—	`conf`	Fair Semi-supervised Representation Learning for Tabular Data Classification. SEBD Shuyi Yang, Mattia Cerrato, Dino Ienco, Ruggero G. Pensa, Roberto Esposito
2023	J	`jnl`	FairSwiRL: fair semi-supervised classification with representation learning. Mach. Learn. Shuyi Yang, Mattia Cerrato, Dino Ienco, Ruggero G. Pensa, Roberto Esposito
2023	B	`conf`	Hierarchical priors for Hyperspherical Prototypical Networks. ESANN Samuele Fonio, Lorenzo Paletto, Mattia Cerrato, Dino Ienco, Roberto Esposito
2023	A*	`conf`	Invariant Representations with Stochastically Quantized Neural Networks. AAAI Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer
2023	J	`jnl`	Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. CoRR Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer
2023	B	`conf`	Privacy-Preserving Learning of Random Forests Without Revealing the Trees. DS Lukas-Malte Bammert, Stefan Kramer, Mattia Cerrato, Ernst Althaus
2023	—	`conf`	The Case for Correctability in Fair Machine Learning. EWAF Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel
2022	J	`jnl`	Fair Group-Shared Representations with Normalizing Flows. CoRR Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer
2022	J	`jnl`	Fair Interpretable Learning via Correction Vectors. CoRR Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer
2022	J	`jnl`	Fair Interpretable Representation Learning with Correction Vectors. CoRR Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer
2022	J	`jnl`	Invariant Representations with Stochastically Quantized Neural Networks. CoRR Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer
2021	J	`jnl`	Ranking Algorithms for Word Ordering in Surface Realization. Inf. Alessandro Mazzei, Mattia Cerrato, Roberto Esposito, Valerio Basile
2020	Misc	`conf`	Constraining deep representations with a noise module for fair classification. SAC Mattia Cerrato, Roberto Esposito, Laura Li Puma
2020	B	`conf`	Fair pairwise learning to rank. DSAA Mattia Cerrato, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer
2020	J	`jnl`	Partitioned Least Squares. CoRR Roberto Esposito, Mattia Cerrato, Marco Locatelli
2019	—	`conf`	Partitioned Least Squares. AI*IA Roberto Esposito, Mattia Cerrato, Marco Locatelli
2019	B	`conf`	Taxonomic and Whole Object Constraints: A Deep Architecture. CogSci Mattia Cerrato, Edoardo Arnaudo, Valentina Gliozzi, Roberto Esposito