Ferdinando Fioretto

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 115

Top Venues

CoRR

AAMAS

IJCAI

Publications

Jacob K. Christopher, Stephen Baek, Ferdinando Fioretto
Projected Generative Diffusion Models for Constraint Satisfaction. CoRR (2024)
James Kotary, Ferdinando Fioretto
Learning Constrained Optimization with Deep Augmented Lagrangian Methods. CoRR (2024)
Prakhar Ganesh, Cuong Tran, Reza Shokri, Ferdinando Fioretto
The Data Minimization Principle in Machine Learning. CoRR (2024)
Ethan King, James Kotary, Ferdinando Fioretto, Ján Drgona
Metric Learning to Accelerate Convergence of Operator Splitting Methods for Differentiable Parametric Programming. CoRR (2024)
My H. Dinh, James Kotary, Ferdinando Fioretto
Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages. FAccT (2024)
Saswat Das, Marco Romanelli, Ferdinando Fioretto
Disparate Impact on Group Accuracy of Linearization for Private Inference. CoRR (2024)
My H. Dinh, James Kotary, Ferdinando Fioretto
Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages. CoRR (2024)
My H. Dinh, James Kotary, Ferdinando Fioretto
End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty. CoRR (2024)
Saswat Das, Keyu Zhu, Christine Task, Pascal Van Hentenryck, Ferdinando Fioretto
Finding ε and δ of Traditional Disclosure Control Systems. AAAI (2024)
Saswat Das, Marco Romanelli, Cuong Tran, Zarreen Reza, Bhavya Kailkhura, Ferdinando Fioretto
Low-rank finetuning for LLMs: A fairness perspective. CoRR (2024)
James Kotary, My H. Dinh, Ferdinando Fioretto
Folded Optimization for End-to-End Model-Based Learning. CoRR (2023)
Cuong Tran, Ferdinando Fioretto
On the Fairness Impacts of Private Ensembles Models. CoRR (2023)
James Kotary, My H. Dinh, Ferdinando Fioretto
Backpropagation of Unrolled Solvers with Folded Optimization. IJCAI (2023)
Cuong Tran, Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles. IJCAI (2023)
James Kotary, Vincenzo Di Vito, Ferdinando Fioretto
Differentiable Model Selection for Ensemble Learning. IJCAI (2023)
James Kotary, Vincenzo Di Vito, Jacob Christopher, Pascal Van Hentenryck, Ferdinando Fioretto
Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization. CoRR (2023)
My H. Dinh, Ferdinando Fioretto
Context-Aware Differential Privacy for Language Modeling. CoRR (2023)
Cuong Tran, Ferdinando Fioretto
Data Minimization at Inference Time. CoRR (2023)
Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck, Saswat Das, Christine Task
Privacy and Bias Analysis of Disclosure Avoidance Systems. CoRR (2023)
Jayanta Mandi, James Kotary, Senne Berden, Maxime Mulamba, Victor Bucarey, Tias Guns, Ferdinando Fioretto
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities. CoRR (2023)
James Kotary, Vincenzo Di Vito, Ferdinando Fioretto
End-to-End Optimization and Learning for Multiagent Ensembles. AAMAS (2023)
Vladimir Dvorkin, Ferdinando Fioretto
Price-Aware Deep Learning for Electricity Markets. CoRR (2023)
Cuong Tran, Ferdinando Fioretto
Personalized Privacy Auditing and Optimization at Test Time. CoRR (2023)
James Kotary, Jacob Christopher, My H. Dinh, Ferdinando Fioretto
Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization. CoRR (2023)
Sree Harsha Nelaturu, Nishaanth Kanna Ravichandran, Cuong Tran, Sara Hooker, Ferdinando Fioretto
On The Fairness Impacts of Hardware Selection in Machine Learning. CoRR (2023)
Khang Tran, Ferdinando Fioretto, Issa Khalil, My T. Thai, NhatHai Phan
FairDP: Certified Fairness with Differential Privacy. CoRR (2023)
Cuong Tran, Ferdinando Fioretto
On the Fairness Impacts of Private Ensembles Models. IJCAI (2023)
Mostafa Mohammadian, Kyri Baker, Ferdinando Fioretto
Gradient-Enhanced Physics-Informed Neural Networks for Power Systems Operational Support. CoRR (2022)
Lesia Mitridati, Emma Romei, Gabriela Hug, Ferdinando Fioretto
Differentially-Private Heat and Electricity Markets Coordination. CoRR (2022)
Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu
Pruning has a disparate impact on model accuracy. NeurIPS (2022)
Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt J. Kusner, Jessica Schrouff
Algorithmic Fairness through the Lens of Causality and Privacy (AFCP) 2022. AFCP (2022)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method. AAAI (2022)
Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck
Post-processing of Differentially Private Data: A Fairness Perspective. CoRR (2022)
Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck, Keyu Zhu
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey. IJCAI (2022)
Ferdinando Fioretto
Integrating Machine Learning and Optimization to Boost Decision Making. IJCAI (2022)
Cuong Tran, Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck
Fairness Increases Adversarial Vulnerability. CoRR (2022)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Ziwei Zhu
End-to-End Learning for Fair Ranking Systems. WWW (2022)
James Kotary, Vincenzo Di Vito, Ferdinando Fioretto
End-to-End Optimization and Learning for Multiagent Ensembles. CoRR (2022)
Cuong Tran, Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles. CoRR (2022)
Sawinder Kaur, Ferdinando Fioretto, Asif Salekin
Deadwooding: Robust Global Pruning for Deep Neural Networks. CoRR (2022)
Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck, Keyu Zhu
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey. CoRR (2022)
Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck
Post-processing of Differentially Private Data: A Fairness Perspective. IJCAI (2022)
Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu
Pruning has a disparate impact on model accuracy. CoRR (2022)
Khoi D. Hoang, Ferdinando Fioretto, Ping Hou, William Yeoh, Makoto Yokoo, Roie Zivan
Proactive Dynamic Distributed Constraint Optimization Problems. J. Artif. Intell. Res. 74 (2022)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Ziwei Zhu
End-to-end Learning for Fair Ranking Systems. CoRR (2021)
My H. Dinh, Ferdinando Fioretto, Mostafa Mohammadian, Kyri Baker
Towards Understanding the Unreasonable Effectiveness of Learning AC-OPF Solutions. CoRR (2021)
Anudit Nagar, Cuong Tran, Ferdinando Fioretto
A Privacy-Preserving and Trustable Multi-agent Learning Framework. CoRR (2021)
Terrence W. K. Mak, Ferdinando Fioretto, Pascal Van Hentenryck
Load Embeddings for Scalable AC-OPF Learning. CoRR (2021)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder
End-to-End Constrained Optimization Learning: A Survey. CoRR (2021)
Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck
Decision Making with Differential Privacy under a Fairness Lens. CoRR (2021)
Ferdinando Fioretto, Pascal Van Hentenryck, Keyu Zhu
Differential privacy of hierarchical Census data: An optimization approach. Artif. Intell. 296 (2021)
Anudit Nagar, Cuong Tran, Ferdinando Fioretto
Privacy-Preserving and Accountable Multi-agent Learning. AAMAS (2021)
Ferdinando Fioretto
Constrained-Based Differential Privacy (Invited Talk). CP (2021)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck, Bryan Wilder
End-to-End Constrained Optimization Learning: A Survey. IJCAI (2021)
Cuong Tran, My H. Dinh, Ferdinando Fioretto
Differentially Private Deep Learning under the Fairness Lens. CoRR (2021)
Cuong Tran, My H. Dinh, Kyle Beiter, Ferdinando Fioretto
A Fairness Analysis on Private Aggregation of Teacher Ensembles. CoRR (2021)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck
Learning Hard Optimization Problems: A Data Generation Perspective. NeurIPS (2021)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method. CoRR (2021)
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck
Learning Hard Optimization Problems: A Data Generation Perspective. CoRR (2021)
Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck, Zhiyan Yao
Decision Making with Differential Privacy under a Fairness Lens. IJCAI (2021)
Keyu Zhu, Pascal Van Hentenryck, Ferdinando Fioretto
Bias and Variance of Post-processing in Differential Privacy. AAAI (2021)
Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach. AAAI (2021)
Cuong Tran, My H. Dinh, Ferdinando Fioretto
Differentially Private Empirical Risk Minimization under the Fairness Lens. NeurIPS (2021)
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods. AAAI (2020)
Ferdinando Fioretto, Pascal Van Hentenryck
OptStream: Releasing Time Series Privately (Extended Abstract). IJCAI (2020)
Vladimir Dvorkin, Ferdinando Fioretto, Pascal Van Hentenryck, Jalal Kazempour, Pierre Pinson
Differentially Private Optimal Power Flow for Distribution Grids. CoRR (2020)
Atena M. Tabakhi, William Yeoh, Ferdinando Fioretto
The Smart Appliance Scheduling Problem: A Bayesian Optimization Approach. PRIMA (2020)
Grace Bang, Guy Barash, Ryan Beal, Jacques Calì, Mauricio Castillo-Effen, Xin Cynthia Chen, Niyati Chhaya, Rachel Cummings, Rohan Dhoopar, Sebastijan Dumancic, Huáscar Espinoza, Eitan Farchi, Ferdinando Fioretto, Raquel Fuentetaja, Christopher William Geib, Odd Erik Gundersen, José Hernández-Orallo, Xiaowei Huang, Kokil Jaidka, Sarah Keren, Seokhwan Kim, Michel Galley, Xiaomo Liu, Tyler Lu, Zhiqiang Ma, Richard Mallah, John McDermid, Martin Michalowski, Reuth Mirsky, Seán Ó hÉigeartaigh, Deepak Ramachandran, Javier Segovia Aguas, Onn Shehory, Arash Shaban-Nejad, Vered Shwartz, Siddharth Srivastava, Kartik Talamadupula, Jian Tang, Pascal Van Hentenryck, Dell Zhang, Jian Zhang
The Association for the Advancement of Artificial Intelligence 2020 Workshop Program. AI Mag. 41 (4) (2020)
Ferdinando Fioretto, Pascal Van Hentenryck, Keyu Zhu
Differential Privacy of Hierarchical Census Data: An Optimization Approach. CoRR (2020)
Ferdinando Fioretto, Lesia Mitridati, Pascal Van Hentenryck
Differential Privacy for Stackelberg Games. IJCAI (2020)
Vladimir Dvorkin, Ferdinando Fioretto, Pascal Van Hentenryck, Jalal Kazempour, Pierre Pinson
Differentially Private Convex Optimization with Feasibility Guarantees. CoRR (2020)
Minas Chatzos, Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
High-Fidelity Machine Learning Approximations of Large-Scale Optimal Power Flow. CoRR (2020)
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
Bilevel Optimization for Differentially Private Optimization. CoRR (2020)
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
Differential Privacy for Power Grid Obfuscation. IEEE Trans. Smart Grid 11 (2) (2020)
Ferdinando Fioretto, Pascal Van Hentenryck, Terrence W. K. Mak, Cuong Tran, Federico Baldo, Michele Lombardi
Lagrangian Duality for Constrained Deep Learning. ECML/PKDD (5) (2020)
Keyu Zhu, Pascal Van Hentenryck, Ferdinando Fioretto
Bias and Variance of Post-processing in Differential Privacy. CoRR (2020)
Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach. CoRR (2020)
Ferdinando Fioretto, Lesia Mitridati, Pascal Van Hentenryck
Differential Privacy for Stackelberg Games. CoRR (2020)
Ferdinando Fioretto, Terrence W. K. Mak, Federico Baldo, Michele Lombardi, Pascal Van Hentenryck
A Lagrangian Dual Framework for Deep Neural Networks with Constraints. CoRR (2020)
Ferdinando Fioretto, Pascal Van Hentenryck
Privacy-Preserving Federated Data Sharing. AAMAS (2019)
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
Privacy-Preserving Obfuscation of Critical Infrastructure Networks. IJCAI (2019)
Terrence W. K. Mak, Ferdinando Fioretto, Pascal Van Hentenryck
Privacy-Preserving Obfuscation for Distributed Power Systems. CoRR (2019)
Ferdinando Fioretto, Pascal Van Hentenryck
Differential Privacy of Hierarchical Census Data: An Optimization Approach. CP (2019)
Ferdinando Fioretto, Pascal Van Hentenryck
OptStream: Releasing Time Series Privately. J. Artif. Intell. Res. 65 (2019)
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
Privacy-Preserving Obfuscation of Critical Infrastructure Networks. CoRR (2019)
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
Differential Privacy for Power Grid Obfuscation. CoRR (2019)
Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods. CoRR (2019)
Ferdinando Fioretto, Lesia Mitridati, Pascal Van Hentenryck
PPSM: A Privacy-Preserving Stackelberg Mechanism: Privacy Guarantees for the Coordination of Sequential Electricity and Gas Markets. CoRR (2019)
Ferdinando Fioretto, Pascal Van Hentenryck
Differential Private Stream Processing of Energy Consumption. CoRR (2018)
Ferdinando Fioretto, Agostino Dovier, Enrico Pontelli
Distributed multi-agent optimization for smart grids and home automation. Intelligenza Artificiale 12 (2) (2018)
Ferdinando Fioretto, Hong Xu, Sven Koenig, T. K. Satish Kumar
Solving Multiagent Constraint Optimization Problems on the Constraint Composite Graph. PRIMA (2018)
Ferdinando Fioretto, Enrico Pontelli
Past and present (and future) of parallel and distributed computation in (constraint) logic programming. Theory Pract. Log. Program. 18 (5-6) (2018)
Khoi D. Hoang, Ferdinando Fioretto, William Yeoh, Enrico Pontelli, Roie Zivan
A Large Neighboring Search Schema for Multi-agent Optimization. CP (2018)
Ferdinando Fioretto, Enrico Pontelli, William Yeoh, Rina Dechter
Accelerating exact and approximate inference for (distributed) discrete optimization with GPUs. Constraints An Int. J. 23 (1) (2018)
Ferdinando Fioretto, Hong Xu, Sven Koenig, T. K. Satish Kumar
Constraint Composite Graph-Based Lifted Message Passing for Distributed Constraint Optimization Problems. ISAIM (2018)
Ferdinando Fioretto, Chansoo Lee, Pascal Van Hentenryck
Constrained-Based Differential Privacy for Mobility Services. AAMAS (2018)
Ferdinando Fioretto, Enrico Pontelli, William Yeoh
Distributed Constraint Optimization Problems and Applications: A Survey. J. Artif. Intell. Res. 61 (2018)
Ferdinando Fioretto, Pascal Van Hentenryck
Constrained-Based Differential Privacy: Releasing Optimal Power Flow Benchmarks Privately - Releasing Optimal Power Flow Benchmarks Privately. CPAIOR (2018)
Ferdinando Fioretto, William Yeoh
AI buzzwords explained: distributed constraint optimization problems. AI Matters 3 (4) (2018)
Ferdinando Fioretto, William Yeoh, Enrico Pontelli
A Multiagent System Approach to Scheduling Devices in Smart Homes. AAMAS (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ferdinando Fioretto