2025
RCCDA: Adaptive Model Updates in the Presence of Concept Drift under a Constrained Resource Budget
NeurIPS 2025poster
Machine learning (ML) algorithms deployed in real-world environments are often faced with the challenge of adapting models to concept drift, where the task data distributions are shifting over time. The problem becomes even more difficult when model performance must be maintained under adherence to…