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

, , , , , и . AFCP, том 214 из Proceedings of Machine Learning Research, стр. 1-6. PMLR, (2022)

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Ferdinando Marinelli

Ferdinando Poli

Ferdinando Giuseppe Menga

 

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A Distributed Constraint Optimization (DCOP) Approach to the Economic Dispatch with Demand Response., , , , и . AAMAS, стр. 999-1007. ACM, (2017)Differential Privacy for Stackelberg Games., , и . CoRR, (2020)Privacy and Bias Analysis of Disclosure Avoidance Systems., , , , и . CoRR, (2023)A Filtering Technique for Fragment Assembly- Based Proteins Loop Modeling with Constraints., , , , и . CP, том 7514 из Lecture Notes in Computer Science, стр. 850-866. Springer, (2012)Differentiable Model Selection for Ensemble Learning., , и . IJCAI, стр. 1954-1962. ijcai.org, (2023)Exploiting GPUs in Solving (Distributed) Constraint Optimization Problems with Dynamic Programming., , , , и . CP, том 9255 из Lecture Notes in Computer Science, стр. 121-139. Springer, (2015)Preference Elicitation for DCOPs., , , и . CP, том 10416 из Lecture Notes in Computer Science, стр. 278-296. Springer, (2017)Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey., , , и . IJCAI, стр. 5470-5477. ijcai.org, (2022)End-to-End Constrained Optimization Learning: A Survey., , , и . IJCAI, стр. 4475-4482. ijcai.org, (2021)Privacy-Preserving and Accountable Multi-agent Learning., , и . AAMAS, стр. 1605-1606. ACM, (2021)