Amal Saadallah

33 papers A* 4B 4C 1Journal 8Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Adaptive Fine-Tuning via Pattern Specialization for Deep Time Series Forecasting. AALTD@ECML/PKDD Amal Saadallah, Abdulaziz Al-Ademi
2025	J	`jnl`	Adaptive Fine-Tuning via Pattern Specialization for Deep Time Series Forecasting. CoRR Amal Saadallah, Abdulaziz Al-Ademi
2025	—	`conf`	SHAP-Guided Regularization in Machine Learning Models. xAI (Late-breaking Work, Demos, Doctoral Consortium) Amal Saadallah
2025	J	`jnl`	SHAP-Guided Regularization in Machine Learning Models. CoRR Amal Saadallah
2024	A*	`conf`	AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting. KDD Raphael Fischer, Amal Saadallah
2024	J	`jnl`	Explainable Adaptive Tree-based Model Selection for Time Series Forecasting. CoRR Matthias Jakobs, Amal Saadallah
2024	—	`conf`	Online Adaptive Local Interpretable Tree Ensembles for Time Series Forecasting. ICDM (Workshops) Amal Saadallah
2024	—	`conf`	Online Explainable Ensemble of Tree Models Pruning for Time Series Forecasting. xAI (Late-breaking Work, Demos, Doctoral Consortium) Amal Saadallah
2024	—	`conf`	Online Explainable Forecasting using Regions of Competence. TempXAI@PKDD/ECML Amal Saadallah, Matthias Jakobs
2024	—	`ed.`	Proceedings of the Workshop on Explainable AI for Time Series and Data Streams (TempXAI 2024) co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, September 9th, 2024. TempXAI@PKDD/ECML Zahraa S. Abdallah, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, Matthias Jakobs, Emmanuel Müller, Maximilian Muschalik, Panagiotis Papapetrou, Amal Saadallah, George Tzagkarakis
2024	—	`ed.`	Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, September 9th, 2024. IAL@PKDD/ECML Mirko Bunse, Marek Herde, Georg Krempl, Vincent Lemaire, Alaa Tharwat, Minh Tuan Pham, Amal Saadallah
2023	J	`jnl`	AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting. CoRR Raphael Fischer, Amal Saadallah
2023	A*	`conf`	Explainable Adaptive Tree-based Model Selection for Time-Series Forecasting. ICDM Matthias Jakobs, Amal Saadallah
2023	—	`conf`	Online Deep Hybrid Ensemble Learning for Time Series Forecasting. ECML/PKDD (5) Amal Saadallah, Matthias Jakobs
2023	B	`conf`	Online Explainable Model Selection for Time Series Forecasting. DSAA Amal Saadallah
2023	—	`ed.`	Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), Torino, Italy, September 22nd, 2023. IAL@PKDD/ECML Mirko Bunse, Barbara Hammer, Georg Krempl, Vincent Lemaire, Alaa Tharwat, Amal Saadallah
2023	—	`conf`	Tutorial: Interactive Adaptive Learning. IAL@PKDD/ECML Mirko Bunse, Georg Krempl, Alaa Tharwat, Amal Saadallah
2022	—	`—`	Explainable adaptation of time series forecasting. Amal Saadallah
2022	J	`jnl`	Explainable online ensemble of deep neural network pruning for time series forecasting. Mach. Learn. Amal Saadallah, Matthias Jakobs, Katharina Morik
2022	—	`conf`	Online Adaptive Multivariate Time Series Forecasting. ECML/PKDD (6) Amal Saadallah, Hanna Mykula, Katharina Morik
2022	—	`ch.`	Quality Assurance in Interlinked Manufacturing Processes. Mach. Learn. under Resour. Constraints Vol. 3 (3) Jochen Deuse, Katharina Morik, Amal Saadallah, Jan Büscher, Thorben Panusch
2022	—	`ch.`	Simulation and Machine Learning. Mach. Learn. under Resour. Constraints Vol. 3 (3) Petra Wiederkehr, Katharina Morik, Amal Saadallah, Felix Finkeldey
2022	J	`jnl`	Simulation and sensor data fusion for machine learning application. Adv. Eng. Informatics Amal Saadallah, Felix Finkeldey, Jens Buß, Katharina Morik, Petra Wiederkehr, Wolfgang Rhode
2021	A*	`conf`	An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting. ICDE Amal Saadallah, Maryam Tavakol, Katharina Morik
2021	—	`conf`	Explainable Online Deep Neural Network Selection Using Adaptive Saliency Maps for Time Series Forecasting. ECML/PKDD (1) Amal Saadallah, Matthias Jakobs, Katharina Morik
2021	B	`conf`	Meta-Adversarial Training of Neural Networks for Binary Classification. IJCNN Amal Saadallah, Katharina Morik
2021	B	`conf`	Online Ensemble Aggregation using Deep Reinforcement Learning for Time Series Forecasting. DSAA Amal Saadallah, Katharina Morik
2020	B	`conf`	Active Sampling for Learning Interpretable Surrogate Machine Learning Models. DSAA Amal Saadallah, Katharina Morik
2020	J	`jnl`	BRIGHT - Drift-Aware Demand Predictions for Taxi Networks. IEEE Trans. Knowl. Data Eng. Amal Saadallah, Luís Moreira-Matias, Ricardo Teixeira Sousa, Jihed Khiari, Erik Jenelius, João Gama
2020	J	`jnl`	Real-time prediction of process forces in milling operations using synchronized data fusion of simulation and sensor data. Eng. Appl. Artif. Intell. Felix Finkeldey, Amal Saadallah, Petra Wiederkehr, Katharina Morik
2019	—	`conf`	A Drift-Based Dynamic Ensemble Members Selection Using Clustering for Time Series Forecasting. ECML/PKDD (1) Amal Saadallah, Florian Priebe, Katharina Morik
2019	A*	`conf`	BRIGHT - Drift-Aware Demand Predictions for Taxi Networks (Extended Abstract). ICDE Amal Saadallah, Luís Moreira-Matias, Ricardo Teixeira Sousa, Jihed Khiari, Erik Jenelius, João Gama
2019	C	`conf`	Learning Ensembles in the Presence of Imbalanced Classes. ICPRAM Amal Saadallah, Nico Piatkowski, Felix Finkeldey, Petra Wiederkehr, Katharina Morik