Alessandro Castelnovo

Orcid: 0000-0001-5234-1155

According to our database1, Alessandro Castelnovo authored at least 19 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Evaluative Item-Contrastive Explanations in Rankings.
Cogn. Comput., November, 2024

Counterfactual explanations as interventions in latent space.
Data Min. Knowl. Discov., September, 2024

Towards Responsible AI in Banking: Addressing Bias for Fair Decision-Making.
CoRR, 2024

Integrating XAI for Predictive Conflict Analytics.
Proceedings of the Joint Proceedings of the xAI 2024 Late-breaking Work, 2024

Augmenting XAI with LLMs: A Case Study in Banking Marketing Recommendation.
Proceedings of the Explainable Artificial Intelligence, 2024

2023
Fair Enough? A map of the current limitations of the requirements to have "fair" algorithms.
CoRR, 2023

Leveraging Group Contrastive Explanations for Handling Fairness.
Proceedings of the Explainable Artificial Intelligence, 2023

Bias On Demand: Investigating Bias with a Synthetic Data Generator.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

An Open-Source Toolkit to Generate Biased Datasets.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Preserving Utility in Fair Top-k Ranking with Intersectional Bias.
Proceedings of the Advances in Bias and Fairness in Information Retrieval, 2023

Marrying LLMs with Domain Expert Validation for Causal Graph Generation (short paper).
Proceedings of the 3rd Italian Workshop on Artificial Intelligence and Applications for Business and Industries (AIABI 2023) co-located with 22nd International Conference of the Italian Association for Artificial Intelligence (AI*IA 2023), 2023

2022
FFTree: A flexible tree to handle multiple fairness criteria.
Inf. Process. Manag., 2022

Extending Decision Tree to Handle Multiple Fairness Criteria.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Leveraging Causal Relations to Provide Counterfactual Explanations and Feasible Recommendations to End Users.
Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

Investigating Bias with a Synthetic Data Generator: Empirical Evidence and Philosophical Interpretation.
Proceedings of 1st Workshop on Bias, 2022

2021
The zoo of Fairness metrics in Machine Learning.
CoRR, 2021

Towards Fairness Through Time.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

2020
BeFair: Addressing Fairness in the Banking Sector.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020


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