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2020 – today
- 2024
[j5]Lucas Rizzo
, Damiano Verda, Serena Berretta, Luca Longo:
A Novel Integration of Data-Driven Rule Generation and Computational Argumentation for Enhanced Explainable AI. Mach. Learn. Knowl. Extr. 6(3): 2049-2073 (2024)- 2023
- [j4]Lucas Rizzo, Luca Longo:
Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts. Inf. Fusion 89: 537-566 (2023) - [j3]Lucas Rizzo:
ArgFrame: A multi-layer, web, argument-based framework for quantitative reasoning. Softw. Impacts 17: 100547 (2023) - [c11]Lucas Rizzo:
A Novel Structured Argumentation Framework for Improved Explainability of Classification Tasks. xAI (3) 2023: 399-414 - [i2]Lucas Rizzo, Luca Longo:
A novel structured argumentation framework for improved explainability of classification tasks. CoRR abs/2306.15500 (2023) - 2022
- [i1]Lucas Rizzo, Luca Longo:
Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts. CoRR abs/2206.13959 (2022) - 2021
- [j2]Luca Longo, Lucas Rizzo, Pierpaolo Dondio:
Examining the modelling capabilities of defeasible argumentation and non-monotonic fuzzy reasoning. Knowl. Based Syst. 211: 106514 (2021) - 2020
- [j1]Lucas Rizzo, Luca Longo:
An empirical evaluation of the inferential capacity of defeasible argumentation, non-monotonic fuzzy reasoning and expert systems. Expert Syst. Appl. 147: 113220 (2020) - [c10]Bruno Ambrozio, Luca Longo, Lucas Rizzo:
LightGWAS: A Novel Machine Learning Procedure for Genome-Wide Association Study. AICS 2020: 25-36 - [c9]Lucas Rizzo, Pierpaolo Dondio, Luca Longo:
Exploring the potential of defeasible argumentation for quantitative inferences in real-world contexts: An assessment of computational trust. AICS 2020: 37-48 - [c8]Giulia Vilone, Lucas Rizzo, Luca Longo:
A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence. AICS 2020: 85-96 - [e1]Luca Longo, Lucas Rizzo, Elizabeth Hunter, Arjun Pakrashi:
Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Republic of Ireland, December 7-8, 2020. CEUR Workshop Proceedings 2771, CEUR-WS.org 2020 [contents]
2010 – 2019
- 2018
- [c7]Lucas Rizzo, Luca Longo:
A Qualitative Investigation of the Explainability of Defeasible Argumentation and Non-Monotonic Fuzzy Reasoning. AICS 2018: 138-149 - [c6]Lucas Rizzo, Luca Longo:
Inferential Models of Mental Workload with Defeasible Argumentation and Non-monotonic Fuzzy Reasoning: a Comparative Study. AI³@AI*IA 2018: 11-26 - [c5]Lucas Rizzo, Ljiljana Majnaric, Luca Longo:
A Comparative Study of Defeasible Argumentation and Non-monotonic Fuzzy Reasoning for Elderly Survival Prediction Using Biomarkers. AI*IA 2018: 197-209 - [c4]Lucas Rizzo, Ljiljana Majnaric, Pierpaolo Dondio, Luca Longo:
An Investigation of Argumentation Theory for the Prediction of Survival in Elderly Using Biomarkers. AIAI 2018: 385-397 - 2017
- [c3]Lucas Rizzo, Luca Longo:
Representing and Inferring Mental Workload via Defeasible Reasoning: A Comparison with the NASA Task Load Index and the Workload Profile. AI³@AI*IA 2017: 126-140 - [c2]Lucas Rizzo:
On Demonstrating the Impact of Defeasible Reasoning in Practice via a Multi-layer Argument-based Framework. AAMAS 2017: 1857-1858 - 2016
- [c1]Lucas Rizzo, Pierpaolo Dondio, Sarah Jane Delany, Luca Longo:
Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile. AIAI 2016: 215-229
Coauthor Index
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last updated on 2024-11-07 21:37 CET by the dblp team
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