| How can I choose an explainer? An application-grounded evaluation of post-hoc explanations S Jesus, C Belém, V Balayan, J Bento, P Saleiro, P Bizarro, J Gama Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021 | 144* | 2021 |
| Turning the tables: Biased, imbalanced, dynamic tabular datasets for ml evaluation S Jesus, J Pombal, D Alves, A Cruz, P Saleiro, R Ribeiro, J Gama, ... Advances in Neural Information Processing Systems 35, 33563-33575, 2022 | 45 | 2022 |
| Fairgbm: Gradient boosting with fairness constraints AF Cruz, C Belém, S Jesus, J Bravo, P Saleiro, P Bizarro arXiv preprint arXiv:2209.07850, 2022 | 24 | 2022 |
| On the importance of application-grounded experimental design for evaluating explainable ml methods K Amarasinghe, KT Rodolfa, S Jesus, V Chen, V Balayan, P Saleiro, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 20921 …, 2024 | 18 | 2024 |
| Addressing bias and fairness in machine learning: A practical guide and hands-on tutorial R Ghani, KT Rodolfa, P Saleiro, S Jesus Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 8 | 2023 |
| Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints JV Alves, D Leitão, S Jesus, MOP Sampaio, J Liébana, P Saleiro, ... arXiv preprint arXiv:2403.06906, 2024 | 4 | 2024 |
| Human-in-the-loop evaluation for explainable artificial intelligence SGP Jesus, CG Belém, V Balayan, DN Polido, JPB Sousa, J Carvalhais, ... US Patent App. 17/382,075, 2022 | 4 | 2022 |
| Aequitas Flow: Streamlining Fair ML Experimentation S Jesus, P Saleiro, BM Jorge, RP Ribeiro, J Gama, P Bizarro, R Ghani arXiv preprint arXiv:2405.05809, 2024 | 2 | 2024 |
| A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies A Martin, V Chen, S Jesus, P Saleiro arXiv preprint arXiv:2302.07444, 2023 | 2 | 2023 |
| FiFAR: A Fraud Detection Dataset for Learning to Defer JV Alves, D Leitão, S Jesus, MOP Sampaio, P Saleiro, MAT Figueiredo, ... arXiv preprint arXiv:2312.13218, 2023 | 1 | 2023 |
| Obtaining a generated dataset with a predetermined bias for evaluating algorithmic fairness of a machine learning model SGP Jesus, DMR dos Santos Marques, JMPRC Pombal, AMF da Cruz, ... US Patent 11,734,612, 2023 | 1 | 2023 |
| Fair-OBNC: Correcting Label Noise for Fairer Datasets S Jesus, H Ferreira, P Saleiro, I Sousa, P Bizarro, C Soares arXiv preprint arXiv:2410.06214, 2024 | | 2024 |
| DeCCaF: Deferral Under Cost and Capacity Constraints Framework JV Alves, D Leitão, S Jesus, MOP Sampaio, P Saleiro, MAT Figueiredo, ... | | |
| fairbench: An Open Benchmark for Fair Machine Learning on Tabular Data AF Cruz, S Jesus, D Alves, J Pombal, J Veiga, C Belém, J Bravo, ... | | |
Pedro SaleiroOpnovaVerified email at opnova.ai
