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Yanou Ramon
Yanou Ramon
QuantumBlack (AI by McKinsey) - PhD in Data Science (University of Antwerp)
Verified email at mckinsey.com - Homepage
Title
Cited by
Cited by
Year
A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C
Y Ramon, D Martens, F Provost, T Evgeniou
Advances in Data Analysis and Classification 14, 801-819, 2020
1152020
Explainable AI for psychological profiling from behavioral data: An application to big five personality predictions from financial transaction records
Y Ramon, RA Farrokhnia, SC Matz, D Martens
Information 12 (12), 518, 2021
242021
Understanding consumer preferences for explanations generated by XAI algorithms
Y Ramon, T Vermeire, O Toubia, D Martens, T Evgeniou
arXiv preprint arXiv:2107.02624, 2021
212021
Deep learning on big, sparse, behavioral data
S De Cnudde, Y Ramon, D Martens, F Provost
Big data 7 (4), 286-307, 2019
122019
Can metafeatures help improve explanations of prediction models when using behavioral and textual data?
Y Ramon, D Martens, T Evgeniou, S Praet
Machine Learning 113 (7), 4245-4284, 2024
112024
Metafeatures-based rule-extraction for classifiers on behavioral and textual data
Y Ramon, D Martens, T Evgeniou, S Praet
arXiv preprint arXiv:2003.04792, 2020
72020
How should artificial intelligence explain itself? understanding preferences for explanations generated by XAI algorithms
Y Ramon, T Vermeire, D Martens, T Evgeniou, O Toubia
Understanding Preferences for Explanations Generated by XAI Algorithms (June …, 2021
52021
The Impact of Cloaking Digital Footprints on User Privacy and Personalization
S Goethals, S Matz, F Provost, Y Ramon, D Martens
arXiv preprint arXiv:2312.15000, 2023
12023
Rule-based explanation methods to gain insight into classification models using behavioral data
Y Ramon
University of Antwerp, 2022
12022
Explainable AI for Psychological Profiling from Digital Footprints: A Case Study of Big Five Personality Predictions from Spending Data
DM Yanou Ramon, Sandra C. Matz, R.A. Farrokhnia
https://arxiv.org/abs/2111.06908, 2021
2021
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