Ferdinando Fioretto
32 papers · 2019–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (8) π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird π Academic Marathon (6)
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Renaissance Researcher
(8)
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Taxonomy Completionist
(39)
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Conference Polyglot
(8)
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Dynamic Duo
(15)
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Grand Slam
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Deep Specialist
(13)
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(3)
ποΈ
Keyword Collector
(107)
β‘
Prolific Year
(6)
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Unstoppable
(7)
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Century Club
(31)
Conferences
IJCAI (13)
AAAI (7)
NIPS (5)
ICML (3)
AISTATS (1)
ICLR (1)
NAACL (1)
UAI (1)
Top co-authors
Research topics
Keywords
differential privacy
(11)
combinatorial optimization
(5)
algorithmic fairness
(4)
constrained optimization
(3)
privacy preservation
(3)
disparate impact
(3)
census datum
(3)
diffusion model
(3)
deep learning
(2)
adversarial robustness
(2)
lagrangian duality
(2)
fairness optimization
(2)
constraint satisfaction
(2)
solution approximation
(2)
group disparity
(2)
supervised learning
(1)
knowledge distillation
(1)
constrained generation
(1)
motion synthesis
(1)
model compression
(1)
Papers
Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning
AAAI 2026
Learning to Solve Differential Equation Constrained Optimization Problems
ICLR 2025
Differentially Private Graph Data Release: Inefficiencies & Unfairness
AISTATS 2025
Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes
AAAI 2025
Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion
NAACL 2025
Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models
ICML 2025
End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty
UAI 2024
On the Effects of Fairness to Adversarial Vulnerability
IJCAI 2024
Constrained Synthesis with Projected Diffusion Models
NIPS 2024
Finding Ξ΅ and Ξ΄ of Traditional Disclosure Control Systems
AAAI 2024
Disparate Impact on Group Accuracy of Linearization for Private Inference
ICML 2024
On The Fairness Impacts of Hardware Selection in Machine Learning
ICML 2024
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles
IJCAI 2023
Backpropagation of Unrolled Solvers with Folded Optimization
IJCAI 2023
Differentiable Model Selection for Ensemble Learning
IJCAI 2023
On the Fairness Impacts of Private Ensembles Models
IJCAI 2023
Data Minimization at Inference Time
NIPS 2023
Post-processing of Differentially Private Data: A Fairness Perspective
IJCAI 2022
Integrating Machine Learning and Optimization to Boost Decision Making
IJCAI 2022
Pruning has a disparate impact on model accuracy
NIPS 2022
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method
AAAI 2022
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey
IJCAI 2022
Learning Hard Optimization Problems: A Data Generation Perspective
NIPS 2021
Differentially Private Empirical Risk Minimization under the Fairness Lens
NIPS 2021
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach
AAAI 2021
Bias and Variance of Post-processing in Differential Privacy
AAAI 2021
Decision Making with Differential Privacy under a Fairness Lens
IJCAI 2021
End-to-End Constrained Optimization Learning: A Survey
IJCAI 2021
OptStream: Releasing Time Series Privately (Extended Abstract)
IJCAI 2020
Differential Privacy for Stackelberg Games
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