David La Barbera
Orcid: 0000-0002-8215-5502
According to our database1,
David La Barbera
authored at least 14 papers
between 2020 and 2024.
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Bibliography
2024
How Many Crowd Workers Do I Need? On Statistical Power when Crowdsourcing Relevance Judgments.
ACM Trans. Inf. Syst., January, 2024
2023
ACM J. Data Inf. Qual., March, 2023
Combining human intelligence and machine learning for fact-checking: Towards a hybrid human-in-the-loop framework.
Intelligenza Artificiale, 2023
Proceedings of the 13th Italian Information Retrieval Workshop (IIR 2023), 2023
2022
HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin-Eosin Whole-Slide Imaging.
J. Imaging, 2022
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022
BUM at CheckThat!-2022: A Composite Deep Learning Approach to Fake News Detection using Evidence Retrieval.
Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th - to, 2022
A Multi-objective Biased Random-Key Genetic Algorithm for the Siting of Emergency Vehicles.
Proceedings of the Metaheuristics - 14th International Conference, 2022
Proceedings of the Sixth Workshop on Natural Language for Artificial Intelligence (NL4AI 2022) co-located with 21th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2022), 2022
2021
The many dimensions of truthfulness: Crowdsourcing misinformation assessments on a multidimensional scale.
Inf. Process. Manag., 2021
HEROHE Challenge: assessing HER2 status in breast cancer without immunohistochemistry or in situ hybridization.
CoRR, 2021
A Software Simulator for Optimizing Ambulance Location and Response Time: A Preliminary Report.
Proceedings of the IEEE International Conference on Digital Health, 2021
2020
Detection of HER2 from Haematoxylin-Eosin Slides Through a Cascade of Deep Learning Classifiers via Multi-Instance Learning.
J. Imaging, 2020
Proceedings of the Advances in Information Retrieval, 2020