Ferdinando Fioretto

Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning AAAI 2026 Learning to Solve Constrained Bilevel Control Co-Design Problems L4DC 2026 Differentially Private Graph Data Release: Inefficiencies & Unfairness AISTATS 2025 Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes AAAI 2025 Learning to Solve Differential Equation Constrained Optimization Problems ICLR 2025 Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models ICML 2025 Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion NAACL 2025 Constrained Synthesis with Projected Diffusion Models NeurIPS 2024 Disparate Impact on Group Accuracy of Linearization for Private Inference ICML 2024 End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty UAI 2024 Finding ε and δ of Traditional Disclosure Control Systems AAAI 2024 On the Effects of Fairness to Adversarial Vulnerability IJCAI 2024 On The Fairness Impacts of Hardware Selection in Machine Learning ICML 2024 Backpropagation of Unrolled Solvers with Folded Optimization IJCAI 2023 Data Minimization at Inference Time NeurIPS 2023 Differentiable Model Selection for Ensemble Learning IJCAI 2023 On the Fairness Impacts of Private Ensembles Models IJCAI 2023 SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles IJCAI 2023 Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey IJCAI 2022 Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method AAAI 2022 Integrating Machine Learning and Optimization to Boost Decision Making IJCAI 2022 Post-processing of Differentially Private Data: A Fairness Perspective IJCAI 2022 Pruning has a disparate impact on model accuracy NeurIPS 2022 Bias and Variance of Post-processing in Differential Privacy AAAI 2021 Decision Making with Differential Privacy under a Fairness Lens IJCAI 2021 Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach AAAI 2021 Differentially Private Empirical Risk Minimization under the Fairness Lens NeurIPS 2021 End-to-End Constrained Optimization Learning: A Survey IJCAI 2021 Learning Hard Optimization Problems: A Data Generation Perspective NeurIPS 2021 Differential Privacy for Stackelberg Games IJCAI 2020 OptStream: Releasing Time Series Privately (Extended Abstract) IJCAI 2020 Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods AAAI 2020 Privacy-Preserving Obfuscation of Critical Infrastructure Networks IJCAI 2019