Adaptive Fine-Tuning via Pattern Specialization for Deep Time Series Forecasting.

Amal Saadallah Technical University of Dortmund, Germany https://orcid.org/0000-0003-2976-7574 Amal Saadallah Abdulaziz Al-Ademi Adaptive Fine-Tuning via Pattern Specialization for Deep Time Series Forecasting. 103-119 2025 AALTD@ECML/PKDD https://doi.org/10.1007/978-3-032-15535-1_7 conf/aaltd/2025 db/conf/aaltd/aaltd2025.html#SaadallahA25 streams/conf/aaltd Amal Saadallah SHAP-Guided Regularization in Machine Learning Models. 9-16 2025 xAI (Late-breaking Work, Demos, Doctoral Consortium) https://ceur-ws.org/Vol-4017/paper_02.pdf conf/xai/2025l db/conf/xai/xai2025l.html#Saadallah25

Amal Saadallah SHAP-Guided Regularization in Machine Learning Models. 2025 July abs/2507.23665 CoRR https://doi.org/10.48550/arXiv.2507.23665 db/journals/corr/corr2507.html#abs-2507-23665 streams/journals/corr

Amal Saadallah Abdulaziz Al-Ademi Adaptive Fine-Tuning via Pattern Specialization for Deep Time Series Forecasting. 2025 August abs/2508.07927 CoRR https://doi.org/10.48550/arXiv.2508.07927 db/journals/corr/corr2508.html#abs-2508-07927 streams/journals/corr

Amal Saadallah Online Adaptive Local Interpretable Tree Ensembles for Time Series Forecasting. 229-237 2024 ICDM (Workshops) https://doi.org/10.1109/ICDMW65004.2024.00036 conf/icdm/2024w db/conf/icdm/icdm2024w.html#Saadallah24 Raphael Fischer 0001 Amal Saadallah AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting. 806-815 2024 KDD https://doi.org/10.1145/3637528.3672057 conf/kdd/2024 db/conf/kdd/kdd2024.html#0001S24 Amal Saadallah Matthias Jakobs Online Explainable Forecasting using Regions of Competence. 7-11 2024 TempXAI@PKDD/ECML https://ceur-ws.org/Vol-3761/extendedabstract2.pdf conf/tempxai/2024 db/conf/tempxai/tempxai2024.html#SaadallahJ24 Amal Saadallah Online Explainable Ensemble of Tree Models Pruning for Time Series Forecasting. 89-96 2024 xAI (Late-breaking Work, Demos, Doctoral Consortium) https://ceur-ws.org/Vol-3793/paper_12.pdf conf/xai/2024l db/conf/xai/xai2024l.html#Saadallah24 Mirko Bunse Marek Herde Georg Krempl Vincent Lemaire 0001 Alaa Tharwat Minh Tuan Pham Amal Saadallah 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 CEUR-WS.org 2024 CEUR Workshop Proceedings 3770 https://ceur-ws.org/Vol-3770 https://nbn-resolving.org/urn:nbn:de:0074-3770-3 db/conf/ial/ial2024.html Zahraa S. Abdallah Fabian Fumagalli Barbara Hammer Eyke Hüllermeier Matthias Jakobs Emmanuel Müller Maximilian Muschalik Panagiotis Papapetrou Amal Saadallah George Tzagkarakis 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 CEUR-WS.org 2024 CEUR Workshop Proceedings 3761 https://ceur-ws.org/Vol-3761 https://nbn-resolving.org/urn:nbn:de:0074-3761-3 db/conf/tempxai/tempxai2024.html

Matthias Jakobs Amal Saadallah Explainable Adaptive Tree-based Model Selection for Time Series Forecasting. 2024 abs/2401.01124 CoRR https://doi.org/10.48550/arXiv.2401.01124 db/journals/corr/corr2401.html#abs-2401-01124

Amal Saadallah Online Explainable Model Selection for Time Series Forecasting. 1-10 2023 DSAA https://doi.org/10.1109/DSAA60987.2023.10302609 conf/dsaa/2023 db/conf/dsaa/dsaa2023.html#Saadallah23 Mirko Bunse Georg Krempl Alaa Tharwat Amal Saadallah Tutorial: Interactive Adaptive Learning. 1-8 2023 IAL@PKDD/ECML https://ceur-ws.org/Vol-3470/paper1.pdf conf/ial/2023 db/conf/ial/ial2023.html#BunseKTS23 Matthias Jakobs Amal Saadallah Explainable Adaptive Tree-based Model Selection for Time-Series Forecasting. 180-189 2023 ICDM https://doi.org/10.1109/ICDM58522.2023.00027 conf/icdm/2023 db/conf/icdm/icdm2023.html#JakobsS23 Amal Saadallah Matthias Jakobs Online Deep Hybrid Ensemble Learning for Time Series Forecasting. 156-171 2023 ECML/PKDD (5) https://doi.org/10.1007/978-3-031-43424-2_10 conf/pkdd/2023-5 db/conf/pkdd/pkdd2023-5.html#SaadallahJ23 Mirko Bunse Barbara Hammer Georg Krempl Vincent Lemaire 0001 Alaa Tharwat Amal Saadallah 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 CEUR-WS.org 2023 CEUR Workshop Proceedings 3470 https://ceur-ws.org/Vol-3470 https://nbn-resolving.org/urn:nbn:de:0074-3470-3 db/conf/ial/ial2023.html

Raphael Fischer 0001 Amal Saadallah AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting. 2023 abs/2312.13038 CoRR https://doi.org/10.48550/arXiv.2312.13038 db/journals/corr/corr2312.html#abs-2312-13038

Amal Saadallah Explainable adaptation of time series forecasting. 2022 Technical University of Dortmund, Germany http://hdl.handle.net/2003/41371 https://nbn-resolving.org/urn:nbn:de:101:1-2023051903421811689268 https://d-nb.info/1289823855

Amal Saadallah Felix Finkeldey Jens Buß Katharina Morik Petra Wiederkehr Wolfgang Rhode Simulation and sensor data fusion for machine learning application. 101600 2022 52 Adv. Eng. Informatics https://doi.org/10.1016/j.aei.2022.101600 db/journals/aei/aei52.html#SaadallahFBMWR22

Amal Saadallah Matthias Jakobs Katharina Morik Explainable online ensemble of deep neural network pruning for time series forecasting. 3459-3487 2022 111 Mach. Learn. 9 https://doi.org/10.1007/s10994-022-06218-4 https://www.wikidata.org/entity/Q114955298 db/journals/ml/ml111.html#SaadallahJM22

Amal Saadallah Hanna Mykula Katharina Morik Online Adaptive Multivariate Time Series Forecasting. 19-35 2022 ECML/PKDD (6) https://doi.org/10.1007/978-3-031-26422-1_2 conf/pkdd/2022-6 db/conf/pkdd/pkdd2022-6.html#SaadallahMM22 Jochen Deuse Katharina Morik Amal Saadallah Jan Büscher Thorben Panusch Quality Assurance in Interlinked Manufacturing Processes. 114-135 2022 Mach. Learn. under Resour. Constraints Vol. 3 (3) https://doi.org/10.1515/9783110785982-015 books/degruyter/22/MM2022-3 db/books/collections/MM2022-3.html#DeuseMSBP22 Petra Wiederkehr Katharina Morik Amal Saadallah Felix Finkeldey Simulation and Machine Learning. 157-179 2022 Mach. Learn. under Resour. Constraints Vol. 3 (3) https://doi.org/10.1515/9783110785982-017 books/degruyter/22/MM2022-3 db/books/collections/MM2022-3.html#WiederkehrMSF22 Amal Saadallah Katharina Morik Online Ensemble Aggregation using Deep Reinforcement Learning for Time Series Forecasting. 1-8 2021 DSAA https://doi.org/10.1109/DSAA53316.2021.9564132 conf/dsaa/2021 db/conf/dsaa/dsaa2021.html#SaadallahM21 Amal Saadallah Maryam Tavakol Katharina Morik An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting. 2255-2260 2021 ICDE https://doi.org/10.1109/ICDE51399.2021.00233 conf/icde/2021 db/conf/icde/icde2021.html#SaadallahTM21 Amal Saadallah Katharina Morik Meta-Adversarial Training of Neural Networks for Binary Classification. 1-7 2021 IJCNN https://doi.org/10.1109/IJCNN52387.2021.9534247 conf/ijcnn/2021 db/conf/ijcnn/ijcnn2021.html#SaadallahM21 Amal Saadallah Matthias Jakobs Katharina Morik Explainable Online Deep Neural Network Selection Using Adaptive Saliency Maps for Time Series Forecasting. 404-420 2021 ECML/PKDD (1) https://doi.org/10.1007/978-3-030-86486-6_25 conf/pkdd/2021-1 db/conf/pkdd/pkdd2021-1.html#SaadallahJM21

Felix Finkeldey Amal Saadallah Petra Wiederkehr Katharina Morik Real-time prediction of process forces in milling operations using synchronized data fusion of simulation and sensor data. 103753 2020 94 Eng. Appl. Artif. Intell. https://doi.org/10.1016/j.engappai.2020.103753 db/journals/eaai/eaai94.html#FinkeldeySWM20

Amal Saadallah Luís Moreira-Matias Ricardo Teixeira Sousa Jihed Khiari Erik Jenelius João Gama 0001 BRIGHT - Drift-Aware Demand Predictions for Taxi Networks. 234-245 2020 32 IEEE Trans. Knowl. Data Eng. 2 https://doi.org/10.1109/TKDE.2018.2883616 db/journals/tkde/tkde32.html#SaadallahMSKJG20

Amal Saadallah Katharina Morik Active Sampling for Learning Interpretable Surrogate Machine Learning Models. 264-272 2020 DSAA https://doi.org/10.1109/DSAA49011.2020.00039 conf/dsaa/2020 db/conf/dsaa/dsaa2020.html#SaadallahM20 Amal Saadallah Luís Moreira-Matias Ricardo Teixeira Sousa Jihed Khiari Erik Jenelius João Gama 0001 BRIGHT - Drift-Aware Demand Predictions for Taxi Networks (Extended Abstract). 2145-2146 2019 ICDE https://doi.org/10.1109/ICDE.2019.00267 conf/icde/2019 db/conf/icde/icde2019.html#SaadallahMSKJG19 Amal Saadallah Nico Piatkowski Felix Finkeldey Petra Wiederkehr Katharina Morik Learning Ensembles in the Presence of Imbalanced Classes. 866-873 2019 ICPRAM https://doi.org/10.5220/0007681508660873 conf/icpram/2019 db/conf/icpram/icpram2019.html#SaadallahPFWM19 Amal Saadallah Florian Priebe Katharina Morik A Drift-Based Dynamic Ensemble Members Selection Using Clustering for Time Series Forecasting. 678-694 2019 ECML/PKDD (1) https://doi.org/10.1007/978-3-030-46150-8_40 conf/pkdd/2019-1 db/conf/pkdd/pkdd2019-1.html#SaadallahPM19 Zahraa Said AbdallahZahraa S. Abdallah Abdulaziz Al-Ademi Mirko Bunse Jan Büscher Jens Buß Jochen Deuse Felix Finkeldey Raphael Fischer 0001 Fabian Fumagalli João Gama 0001 Barbara Hammer Marek Herde Eyke Hüllermeier Matthias Jakobs Erik Jenelius Jihed Khiari Georg Krempl Vincent Lemaire 0001 Luís Moreira-Matias Katharina Morik Emmanuel Müller Maximilian Muschalik Hanna Mykula Thorben Panusch Panagiotis Papapetrou Minh Tuan Pham Nico Piatkowski Florian Priebe Wolfgang Rhode Ricardo Teixeira Sousa Maryam Tavakol Alaa Tharwat George Tzagkarakis Petra Wiederkehr