Amal Saadallah

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 20

Top Topics

Model Selection

Top Venues

Publications

Matthias Jakobs, Amal Saadallah
Explainable Adaptive Tree-based Model Selection for Time Series Forecasting. CoRR (2024)
Raphael Fischer, Amal Saadallah
AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting. KDD (2024)
Mirko Bunse, Georg Krempl, Alaa Tharwat, Amal Saadallah
Tutorial: Interactive Adaptive Learning. IAL@PKDD/ECML (2023)
Matthias Jakobs, Amal Saadallah
Explainable Adaptive Tree-based Model Selection for Time-Series Forecasting. ICDM (2023)
Amal Saadallah, Matthias Jakobs
Online Deep Hybrid Ensemble Learning for Time Series Forecasting. ECML/PKDD (5) (2023)
Amal Saadallah
Online Explainable Model Selection for Time Series Forecasting. DSAA (2023)
Raphael Fischer, Amal Saadallah
AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting. CoRR (2023)
Amal Saadallah, Hanna Mykula, Katharina Morik
Online Adaptive Multivariate Time Series Forecasting. ECML/PKDD (6) (2022)
Amal Saadallah, Felix Finkeldey, Jens Buß, Katharina Morik, Petra Wiederkehr, Wolfgang Rhode
Simulation and sensor data fusion for machine learning application. Adv. Eng. Informatics 52 (2022)
Amal Saadallah, Matthias Jakobs, Katharina Morik
Explainable online ensemble of deep neural network pruning for time series forecasting. Mach. Learn. 111 (9) (2022)
Amal Saadallah, Katharina Morik
Online Ensemble Aggregation using Deep Reinforcement Learning for Time Series Forecasting. DSAA (2021)
Amal Saadallah, Maryam Tavakol, Katharina Morik
An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting. ICDE (2021)
Amal Saadallah, Katharina Morik
Meta-Adversarial Training of Neural Networks for Binary Classification. IJCNN (2021)
Amal Saadallah, Matthias Jakobs, Katharina Morik
Explainable Online Deep Neural Network Selection Using Adaptive Saliency Maps for Time Series Forecasting. ECML/PKDD (1) (2021)
Amal Saadallah, Katharina Morik
Active Sampling for Learning Interpretable Surrogate Machine Learning Models. DSAA (2020)
Amal Saadallah, Luís Moreira-Matias, Ricardo Sousa, Jihed Khiari, Erik Jenelius, João Gama
BRIGHT - Drift-Aware Demand Predictions for Taxi Networks. IEEE Trans. Knowl. Data Eng. 32 (2) (2020)
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. Eng. Appl. Artif. Intell. 94 (2020)
Amal Saadallah, Nico Piatkowski, Felix Finkeldey, Petra Wiederkehr, Katharina Morik
Learning Ensembles in the Presence of Imbalanced Classes. ICPRAM (2019)
Amal Saadallah, Florian Priebe, Katharina Morik
A Drift-Based Dynamic Ensemble Members Selection Using Clustering for Time Series Forecasting. ECML/PKDD (1) (2019)
Amal Saadallah, Luís Moreira-Matias, Ricardo Sousa, Jihed Khiari, Erik Jenelius, João Gama
BRIGHT - Drift-Aware Demand Predictions for Taxi Networks (Extended Abstract). ICDE (2019)