Ferdinando Fioretto

Orcid: 0000-0002-1381-6776

Affiliations:
  • University of Virginia, Charlottesville, VA, USA


According to our database1, Ferdinando Fioretto authored at least 112 papers between 2012 and 2024.

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Bibliography

2024
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities.
J. Artif. Intell. Res., 2024

Learning To Solve Differential Equation Constrained Optimization Problems.
CoRR, 2024

Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes.
CoRR, 2024

Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion.
CoRR, 2024

Differentially Private Data Release on Graphs: Inefficiencies and Unfairness.
CoRR, 2024

The Data Minimization Principle in Machine Learning.
CoRR, 2024

Low-rank finetuning for LLMs: A fairness perspective.
CoRR, 2024

Metric Learning to Accelerate Convergence of Operator Splitting Methods for Differentiable Parametric Programming.
CoRR, 2024

Learning Constrained Optimization with Deep Augmented Lagrangian Methods.
CoRR, 2024

End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty.
CoRR, 2024

Projected Generative Diffusion Models for Constraint Satisfaction.
CoRR, 2024

On the Effects of Fairness to Adversarial Vulnerability.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

On The Fairness Impacts of Hardware Selection in Machine Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Disparate Impact on Group Accuracy of Linearization for Private Inference.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Learning Joint Models of Prediction and Optimization.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Finding ε and δ of Traditional Disclosure Control Systems.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization.
CoRR, 2023

Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization.
CoRR, 2023

Price-Aware Deep Learning for Electricity Markets.
CoRR, 2023

FairDP: Certified Fairness with Differential Privacy.
CoRR, 2023

Personalized Privacy Auditing and Optimization at Test Time.
CoRR, 2023

Context-Aware Differential Privacy for Language Modeling.
CoRR, 2023

Privacy and Bias Analysis of Disclosure Avoidance Systems.
CoRR, 2023

Folded Optimization for End-to-End Model-Based Learning.
CoRR, 2023

Data Minimization at Inference Time.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Differentiable Model Selection for Ensemble Learning.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Backpropagation of Unrolled Solvers with Folded Optimization.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

On the Fairness Impacts of Private Ensembles Models.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

End-to-End Optimization and Learning for Multiagent Ensembles.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
Proactive Dynamic Distributed Constraint Optimization Problems.
J. Artif. Intell. Res., 2022

Fairness Increases Adversarial Vulnerability.
CoRR, 2022

Gradient-Enhanced Physics-Informed Neural Networks for Power Systems Operational Support.
CoRR, 2022

Deadwooding: Robust Global Pruning for Deep Neural Networks.
CoRR, 2022

Differentially-Private Heat and Electricity Markets Coordination.
CoRR, 2022

End-to-End Learning for Fair Ranking Systems.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Pruning has a disparate impact on model accuracy.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Post-processing of Differentially Private Data: A Fairness Perspective.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Integrating Machine Learning and Optimization to Boost Decision Making.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Algorithmic Fairness through the Lens of Causality and Privacy (AFCP) 2022.
Proceedings of the Algorithmic Fairness through the Lens of Causality and Privacy Workshop, 2022

Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Towards Understanding the Unreasonable Effectiveness of Learning AC-OPF Solutions.
CoRR, 2021

A Fairness Analysis on Private Aggregation of Teacher Ensembles.
CoRR, 2021

Differentially Private Deep Learning under the Fairness Lens.
CoRR, 2021

A Privacy-Preserving and Trustable Multi-agent Learning Framework.
CoRR, 2021

Decision Making with Differential Privacy under a Fairness Lens.
CoRR, 2021

Load Embeddings for Scalable AC-OPF Learning.
CoRR, 2021

Differential privacy of hierarchical Census data: An optimization approach.
Artif. Intell., 2021

Differentially Private Empirical Risk Minimization under the Fairness Lens.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Hard Optimization Problems: A Data Generation Perspective.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

End-to-End Constrained Optimization Learning: A Survey.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Decision Making with Differential Privacy under a Fairness Lens.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Constrained-Based Differential Privacy (Invited Talk).
Proceedings of the 27th International Conference on Principles and Practice of Constraint Programming, 2021

Privacy-Preserving and Accountable Multi-agent Learning.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Bias and Variance of Post-processing in Differential Privacy.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Differential Privacy for Power Grid Obfuscation.
IEEE Trans. Smart Grid, 2020

High-Fidelity Machine Learning Approximations of Large-Scale Optimal Power Flow.
CoRR, 2020

Differentially Private Convex Optimization with Feasibility Guarantees.
CoRR, 2020

Differentially Private Optimal Power Flow for Distribution Grids.
CoRR, 2020

Bilevel Optimization for Differentially Private Optimization.
CoRR, 2020

A Lagrangian Dual Framework for Deep Neural Networks with Constraints.
CoRR, 2020

The Association for the Advancement of Artificial Intelligence 2020 Workshop Program.
AI Mag., 2020

The Smart Appliance Scheduling Problem: A Bayesian Optimization Approach.
Proceedings of the PRIMA 2020: Principles and Practice of Multi-Agent Systems, 2020

Lagrangian Duality for Constrained Deep Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Differential Privacy for Stackelberg Games.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

OptStream: Releasing Time Series Privately (Extended Abstract).
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
OptStream: Releasing Time Series Privately.
J. Artif. Intell. Res., 2019

PPSM: A Privacy-Preserving Stackelberg Mechanism: Privacy Guarantees for the Coordination of Sequential Electricity and Gas Markets.
CoRR, 2019

Privacy-Preserving Obfuscation for Distributed Power Systems.
CoRR, 2019

Privacy-Preserving Obfuscation of Critical Infrastructure Networks.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Differential Privacy of Hierarchical Census Data: An Optimization Approach.
Proceedings of the Principles and Practice of Constraint Programming, 2019

Privacy-Preserving Federated Data Sharing.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
Past and present (and future) of parallel and distributed computation in (constraint) logic programming.
Theory Pract. Log. Program., 2018

Distributed Constraint Optimization Problems and Applications: A Survey.
J. Artif. Intell. Res., 2018

Distributed multi-agent optimization for smart grids and home automation.
Intelligenza Artificiale, 2018

Differential Private Stream Processing of Energy Consumption.
CoRR, 2018

Accelerating exact and approximate inference for (distributed) discrete optimization with GPUs.
Constraints An Int. J., 2018

AI buzzwords explained: distributed constraint optimization problems.
AI Matters, 2018

Solving Multiagent Constraint Optimization Problems on the Constraint Composite Graph.
Proceedings of the PRIMA 2018: Principles and Practice of Multi-Agent Systems - 21st International Conference, Tokyo, Japan, October 29, 2018

Constraint Composite Graph-Based Lifted Message Passing for Distributed Constraint Optimization Problems.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2018

Constrained-Based Differential Privacy: Releasing Optimal Power Flow Benchmarks Privately - Releasing Optimal Power Flow Benchmarks Privately.
Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2018

A Large Neighboring Search Schema for Multi-agent Optimization.
Proceedings of the Principles and Practice of Constraint Programming, 2018

Constrained-Based Differential Privacy for Mobility Services.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017
Solving DCOPs with Distributed Large Neighborhood Search.
CoRR, 2017

Preference Elicitation for DCOPs.
Proceedings of the Principles and Practice of Constraint Programming, 2017

A Realistic Dataset for the Smart Home Device Scheduling Problem for DCOPs.
Proceedings of the Autonomous Agents and Multiagent Systems, 2017

Infinite-Horizon Proactive Dynamic DCOPs.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

A Distributed Constraint Optimization (DCOP) Approach to the Economic Dispatch with Demand Response.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

A Multiagent System Approach to Scheduling Devices in Smart Homes.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Exploiting the Structure of Distributed Constraint Optimization Problems.
PhD thesis, 2016

A Dynamic Programming-Based MCMC Framework for Solving DCOPs with GPUs.
Proceedings of the Principles and Practice of Constraint Programming, 2016

ER-DCOPs: A Framework for Distributed Constraint Optimization with Uncertainty in Constraint Utilities.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Proactive Dynamic Distributed Constraint Optimization.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Investigation of Learning Strategies for the SPOT Broker in Power TAC.
Proceedings of the Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets, 2016

Proactive Dynamic DCOPs.
Proceedings of the AI for Smart Grids and Smart Buildings, 2016

Multi-Variable Agents Decomposition for DCOPs.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Constrained Community-Based Gene Regulatory Network Inference.
ACM Trans. Model. Comput. Simul., 2015

Exploiting GPUs in Solving (Distributed) Constraint Optimization Problems with Dynamic Programming.
Proceedings of the Principles and Practice of Constraint Programming, 2015

Large Neighborhood Search with Quality Guarantees for Distributed Constraint Optimization Problems.
Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

Multi-Variable Agents Decomposition for DCOPs to Exploit Multi-Level Parallelism.
Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

Exploiting the Structure of Distributed Constraint Optimization Problems.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Exploring the Use of GPUs in Constraint Solving.
Proceedings of the Practical Aspects of Declarative Languages, 2014

A GPU Implementation of Large Neighborhood Search for Solving Constraint Optimization Problems.
Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014

Improving DPOP with Branch Consistency for Solving Distributed Constraint Optimization Problems.
Proceedings of the Principles and Practice of Constraint Programming, 2014

GD-GIBBS: a GPU-based sampling algorithm for solving distributed constraint optimization problems.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

2013
A Constraint Solver for Flexible Protein Model.
J. Artif. Intell. Res., 2013

Constraint Programming in Community-Based Gene Regulatory Network Inference.
Proceedings of the Computational Methods in Systems Biology, 2013

2012
A Filtering Technique for Fragment Assembly- Based Proteins Loop Modeling with Constraints.
Proceedings of the Principles and Practice of Constraint Programming, 2012


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