Fioretto, Ferdinando

42 publications

NeurIPS 2025 Constrained Discrete Diffusion Michael Cardei, Jacob K Christopher, Bhavya Kailkhura, Thomas Hartvigsen, Ferdinando Fioretto

AISTATS 2025 Differentially Private Graph Data Release: Inefficiencies & Unfairness Ferdinando Fioretto, Diptangshu Sen, Juba Ziani

AAAI 2025 Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes Joonhyuk Ko, Juba Ziani, Saswat Das, Matt Williams, Ferdinando Fioretto

ICLR 2025 Learning to Solve Differential Equation Constrained Optimization Problems Vincenzo Di Vito Francesco, Mostafa Mohammadian, Kyri Baker, Ferdinando Fioretto

ICML 2025 Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models Jinhao Liang, Jacob K Christopher, Sven Koenig, Ferdinando Fioretto

NeurIPS 2025 Training-Free Constrained Generation with Stable Diffusion Models Stefano Zampini, Jacob K Christopher, Luca Oneto, Davide Anguita, Ferdinando Fioretto

NeurIPS 2024 Constrained Synthesis with Projected Diffusion Models Jacob K. Christopher, Stephen Baek, Ferdinando Fioretto

JAIR 2024 Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities Jayanta Mandi, James Kotary, Senne Berden, Maxime Mulamba, Victor Bucarey, Tias Guns, Ferdinando Fioretto

ICMLW 2024 Differentiable Approximations of Fair OWA Optimization My H Dinh, James Kotary, Ferdinando Fioretto

ICML 2024 Disparate Impact on Group Accuracy of Linearization for Private Inference Saswat Das, Marco Romanelli, Ferdinando Fioretto

UAI 2024 End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty My H. Dinh, James Kotary, Ferdinando Fioretto

AAAI 2024 Finding Ε and Δ of Traditional Disclosure Control Systems Saswat Das, Keyu Zhu, Christine Task, Pascal Van Hentenryck, Ferdinando Fioretto

IJCAI 2024 On the Effects of Fairness to Adversarial Vulnerability Cuong Tran, Keyu Zhu, Pascal Van Hentenryck, Ferdinando Fioretto

ICML 2024 On the Fairness Impacts of Hardware Selection in Machine Learning Sree Harsha Nelaturu, Nishaanth Kanna Ravichandran, Cuong Tran, Sara Hooker, Ferdinando Fioretto

NeurIPSW 2024 The Data Minimization Principle in Machine Learning Prakhar Ganesh, Cuong Tran, Reza Shokri, Ferdinando Fioretto

IJCAI 2023 Backpropagation of Unrolled Solvers with Folded Optimization James Kotary, My H. Dinh, Ferdinando Fioretto

NeurIPS 2023 Data Minimization at Inference Time Cuong Tran, Ferdinando Fioretto

IJCAI 2023 Differentiable Model Selection for Ensemble Learning James Kotary, Vincenzo Di Vito, Ferdinando Fioretto

IJCAI 2023 On the Fairness Impacts of Private Ensembles Models Cuong Tran, Ferdinando Fioretto

IJCAI 2023 SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles Cuong Tran, Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck

IJCAI 2022 Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck, Keyu Zhu

AAAI 2022 Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck

IJCAI 2022 Integrating Machine Learning and Optimization to Boost Decision Making Ferdinando Fioretto

IJCAI 2022 Post-Processing of Differentially Private Data: A Fairness Perspective Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck

JAIR 2022 Proactive Dynamic Distributed Constraint Optimization Problems Khoi D. Hoang, Ferdinando Fioretto, Ping Hou, William Yeoh, Makoto Yokoo, Roie Zivan

NeurIPS 2022 Pruning Has a Disparate Impact on Model Accuracy Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu

AAAI 2021 Bias and Variance of Post-Processing in Differential Privacy Keyu Zhu, Pascal Van Hentenryck, Ferdinando Fioretto

IJCAI 2021 Decision Making with Differential Privacy Under a Fairness Lens Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck, Zhiyan Yao

NeurIPS 2021 Differentially Private Empirical Risk Minimization Under the Fairness Lens Cuong Tran, My Dinh, Ferdinando Fioretto

AAAI 2021 Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck

IJCAI 2021 End-to-End Constrained Optimization Learning: A Survey James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder

NeurIPS 2021 Learning Hard Optimization Problems: A Data Generation Perspective James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck

IJCAI 2020 Differential Privacy for Stackelberg Games Ferdinando Fioretto, Lesia Mitridati, Pascal Van Hentenryck

ECML-PKDD 2020 Lagrangian Duality for Constrained Deep Learning Ferdinando Fioretto, Pascal Van Hentenryck, Terrence W. K. Mak, Cuong Tran, Federico Baldo, Michele Lombardi

IJCAI 2020 OptStream: Releasing Time Series Privately (Extended Abstract) Ferdinando Fioretto, Pascal Van Hentenryck

AAAI 2020 Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck

JAIR 2019 OptStream: Releasing Time Series Privately Ferdinando Fioretto, Pascal Van Hentenryck

IJCAI 2019 Privacy-Preserving Obfuscation of Critical Infrastructure Networks Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck

JAIR 2018 Distributed Constraint Optimization Problems and Applications: A Survey Ferdinando Fioretto, Enrico Pontelli, William Yeoh

AAAI 2016 Multi-Variable Agents Decomposition for DCOPs Ferdinando Fioretto, William Yeoh, Enrico Pontelli

AAAI 2015 Exploiting the Structure of Distributed Constraint Optimization Problems Ferdinando Fioretto

JAIR 2013 A Constraint Solver for Flexible Protein Model Federico Campeotto, Alessandro Dal Palù, Agostino Dovier, Ferdinando Fioretto, Enrico Pontelli