3 papers
cs.LG2025
Adaptive Fine-Tuning via Pattern Specialization for Deep Time Series Forecasting
Amal Saadallah, Abdulaziz Al-Ademi
Time series forecasting poses significant challenges in non-stationary environments where underlying patterns evolve over time. In this work, we propose a novel framework that enha…
cs.LG2025
SHAP-Guided Regularization in Machine Learning Models
Amal Saadallah
Feature attribution methods such as SHapley Additive exPlanations (SHAP) have become instrumental in understanding machine learning models, but their role in guiding model optimiza…
cs.LG2024
Explainable Adaptive Tree-based Model Selection for Time Series Forecasting
Matthias Jakobs, Amal Saadallah
Tree-based models have been successfully applied to a wide variety of tasks, including time series forecasting. They are increasingly in demand and widely accepted because of their…