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Journal Articles
- 2024
[j3]Roberto Esposito, Mattia Cerrato, Marco Locatelli:
Partitioned least squares. Mach. Learn. 113(9): 6839-6869 (2024)- 2023
- [j2]Shuyi Yang, Mattia Cerrato, Dino Ienco, Ruggero G. Pensa
, Roberto Esposito:
FairSwiRL: fair semi-supervised classification with representation learning. Mach. Learn. 112(9): 3051-3076 (2023) - 2021
- [j1]Alessandro Mazzei, Mattia Cerrato, Roberto Esposito, Valerio Basile:
Ranking Algorithms for Word Ordering in Surface Realization. Inf. 12(8): 337 (2021)
Conference and Workshop Papers
- 2024
- [c11]Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer:
Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. AAAI 2024: 11766-11774 - [c10]Xenia Heilmann, Mattia Cerrato, Ernst Althaus:
Differentially Private Sum-Product Networks. ICML 2024 - 2023
- [c9]Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer:
Invariant Representations with Stochastically Quantized Neural Networks. AAAI 2023: 6962-6970 - [c8]Lukas-Malte Bammert, Stefan Kramer, Mattia Cerrato, Ernst Althaus:
Privacy-Preserving Learning of Random Forests Without Revealing the Trees. DS 2023: 372-386 - [c7]Samuele Fonio, Lorenzo Paletto, Mattia Cerrato, Dino Ienco, Roberto Esposito:
Hierarchical priors for Hyperspherical Prototypical Networks. ESANN 2023 - [c6]Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel:
The Case for Correctability in Fair Machine Learning. EWAF 2023 - [c5]Shuyi Yang, Mattia Cerrato, Dino Ienco, Ruggero G. Pensa, Roberto Esposito:
Fair Semi-supervised Representation Learning for Tabular Data Classification. SEBD 2023: 488-496 - 2020
- [c4]Mattia Cerrato, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer:
Fair pairwise learning to rank. DSAA 2020: 729-738 - [c3]Mattia Cerrato, Roberto Esposito, Laura Li Puma:
Constraining deep representations with a noise module for fair classification. SAC 2020: 470-472 - 2019
- [c2]Roberto Esposito, Mattia Cerrato, Marco Locatelli:
Partitioned Least Squares. AI*IA 2019: 180-192 - [c1]Mattia Cerrato, Edoardo Arnaudo, Valentina Gliozzi, Roberto Esposito:
Taxonomic and Whole Object Constraints: A Deep Architecture. CogSci 2019: 1465-1471
Informal and Other Publications
- 2024
- [i9]Mattia Cerrato, Marius Köppel, Philipp Wolf, Stefan Kramer:
10 Years of Fair Representations: Challenges and Opportunities. CoRR abs/2407.03834 (2024) - [i8]Marius Köppel, Niklas Witzig, Tim Klausmann, Mattia Cerrato, Tobias Schweitzer, Jochen Weber, Erdem Yilmaz, Juan Chimbo, Bernardo del Campo, Lissete Davila, David Barreno:
Predicting NOx emissions in Biochar Production Plants using Machine Learning. CoRR abs/2412.07881 (2024) - 2023
- [i7]Stefan Kramer, Mattia Cerrato, Saso Dzeroski, Ross D. King:
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. CoRR abs/2305.02251 (2023) - [i6]Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer:
Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. CoRR abs/2312.09950 (2023) - 2022
- [i5]Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer:
Fair Group-Shared Representations with Normalizing Flows. CoRR abs/2201.06336 (2022) - [i4]Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer:
Fair Interpretable Learning via Correction Vectors. CoRR abs/2201.06343 (2022) - [i3]Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer:
Fair Interpretable Representation Learning with Correction Vectors. CoRR abs/2202.03078 (2022) - [i2]Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer:
Invariant Representations with Stochastically Quantized Neural Networks. CoRR abs/2208.02656 (2022) - 2020
- [i1]Roberto Esposito, Mattia Cerrato, Marco Locatelli:
Partitioned Least Squares. CoRR abs/2006.16202 (2020)
Coauthor Index
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