
The author explores the importance of adaptive hyperparameter optimization in continual learning scenarios, emphasizing the need for dynamic tuning to improve performance and efficiency.


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adaptive-hyperparameter-optimization-for-continual-learning-scenarios-a-comprehensive-analysis


Adaptive Hyperparameter Optimization for Continual Learning Scenarios: A Comprehensive Analysis


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All the hyperparameter optimization (HPO) frameworks tested, including the commonly used but unrealistic end-of-training HPO, perform similarly in terms of predictive performance. The simplest and most computationally efficient method, first-task HPO, is recommended as the preferred HPO framework for continual learning.


hyperparameter-optimization-strategies-for-continual-learning


Hyperparameter Optimization Strategies for Continual Learning
