Mohamed Maher

According to our database, Mohamed Maher authored at least 12 papers between 2019 and 2025.

Collaborative distances:

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

2025

FedForecaster: An Automated Federated Learning Approach for Time-series Forecasting.

Mohamed Maher, Osama Fayez Oun, Mahmoud Saeed Mesmeh, Radwa El Shawi

Proceedings of the Proceedings 28th International Conference on Extending Database Technology, 2025

SmartCal: A Novel Automated Approach to Classifier Probability Calibration.

Mohamed Maher Abdelrahman, Osama Fayez Oun, Youssef Medhat, Mariam Magdy Elseedawy, Yara Mostafa Marei, Abdullah Ibrahim, Radwa Elshawi

Proceedings of the International Conference on Automated Machine Learning (AutoML 2025), 2025

ML-EvalPro: Machine Learning Evaluation Profiler for Supervised Tasks.

Mohamed Maher, Reem Ayman, Sondos Akram, Omar Marie, Radwa El Shawi

Proceedings of the Artificial Intelligence in Medicine - 23rd International Conference, 2025

2024

AutoMLBench: A comprehensive experimental evaluation of automated machine learning frameworks.

Hassan Eldeeb, Mohamed Maher, Radwa El Shawi, Sherif Sakr

Expert Syst. Appl., 2024

GizaML: A Collaborative Meta-learning Based Framework Using LLM For Automated Time-Series Forecasting.

Esraa Sayed, Mohamed Maher, Omar Sedeek, Ahmed Eldamaty, Amr Kamel, Radwa El Shawi

Proceedings of the Proceedings 27th International Conference on Extending Database Technology, 2024

2022

Comprehensive Empirical Evaluation of Deep Learning Approaches for Session-Based Recommendation in E-Commerce.

Mohamed Maher, Perseverance Munga Ngoy, Aleksandrs Rebriks, Cagri Ozcinar, Josué Cuevas, Rajasekhar Sanagavarapu, Gholamreza Anbarjafari

Entropy, 2022

AutoMLBench: A Comprehensive Experimental Evaluation of Automated Machine Learning Frameworks.

Hassan Eldeeb, Mohamed Maher, Oleh Matsuk, Abdelrahman Aldallal, Radwa El Shawi, Sherif Sakr

CoRR, 2022

2021

Instance-based Label Smoothing For Better Calibrated Classification Networks.

Mohamed Maher, Meelis Kull

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

The impact of Auto-Sklearn's Learning Settings: Meta-learning, Ensembling, Time Budget, and Search Space Size.

Hassan Eldeeb, Oleh Matsuk, Mohamed Maher, Abdelrhman Eldallal, Sherif Sakr

Proceedings of the Workshops of the EDBT/ICDT 2021 Joint Conference, 2021

2019

Automated Machine Learning: State-of-The-Art and Open Challenges.

Radwa El Shawi, Mohamed Maher, Sherif Sakr

CoRR, 2019

MINARET: A Recommendation Framework for Scientific Reviewers.

Sherif Sakr, Mohamed Ragab, Mohamed Maher, Ahmed Awad

Proceedings of the Advances in Database Technology, 2019

SmartML: A Meta Learning-Based Framework for Automated Selection and Hyperparameter Tuning for Machine Learning Algorithms.

Mohamed Maher, Sherif Sakr

Proceedings of the Advances in Database Technology, 2019