Rami Haffar

According to our database, Rami Haffar authored at least 11 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Multi-Task Faces (MTF) dataset.

Rami Haffar

Dataset, May, 2024

Contributions to Explainability and Attack Detection in Deep Learning

Rami Haffar

PhD thesis, 2024

GLOR-FLEX: Local to Global Rule-Based EXplanations for Federated Learning.

Rami Haffar, Francesca Naretto, David Sánchez, Anna Monreale, Josep Domingo-Ferrer

Proceedings of the IEEE International Conference on Fuzzy Systems, 2024

2023

Multi-Task Faces (MTF) Data Set: A Legally and Ethically Compliant Collection of Face Images for Various Classification Tasks.

Rami Haffar, David Sánchez, Josep Domingo-Ferrer

CoRR, 2023

Explaining predictions and attacks in federated learning via random forests.

Rami Haffar, David Sánchez, Josep Domingo-Ferrer

Appl. Intell., 2023

2022

Generating Deep Learning Model-Specific Explanations at the End User's Side.

Rami Haffar, Najeeb Jebreel, David Sánchez, Josep Domingo-Ferrer

Int. J. Uncertain. Fuzziness Knowl. Based Syst., December, 2022

Measuring Fairness in Machine Learning Models via Counterfactual Examples.

Rami Haffar, Ashneet Khandpur Singh, Josep Domingo-Ferrer, Najeeb Jebreel

Proceedings of the Modeling Decisions for Artificial Intelligence, 2022

2021

Explaining Image Misclassification in Deep Learning via Adversarial Examples.

Rami Haffar, Najeeb Moharram Jebreel, Josep Domingo-Ferrer, David Sánchez

Proceedings of the Modeling Decisions for Artificial Intelligence, 2021

2020

Detecting Bad Answers in Survey Data Through Unsupervised Machine Learning.

Najeeb Moharram Jebreel, Rami Haffar, Ashneet Khandpur Singh, David Sánchez, Josep Domingo-Ferrer, Alberto Blanco-Justicia

Proceedings of the Privacy in Statistical Databases, 2020

Explaining Misclassification and Attacks in Deep Learning via Random Forests.

Rami Haffar, Josep Domingo-Ferrer, David Sánchez

Proceedings of the Modeling Decisions for Artificial Intelligence, 2020

2019

Mass Detection in Mammograms Using a Robust Deep Learning Model.

Vivek Kumar Singh, Mohamed Abdel-Nasser, Hatem A. Rashwan, Farhan Akram, Rami Haffar, Nidhi Pandey, Md. Mostafa Kamal Sarker, Sebastian Kohan, Josep Guma, Santiago Romaní, Domenec Puig

Proceedings of the Artificial Intelligence Research and Development, 2019