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Developing a robust generalization measure for the performance of machine learning models is an important and challenging task. A lot of recent research in the area focuses on the model decision boundary when predicting generalization. In this paper, as part of the “Predicting Generalization in Deep Learning” competition, we analyse the complexity of decision boundaries using the concept of fractal dimension and develop a generalization measure based on that technique.

生成讲解博客的中文版本

生成AI智能校验的中文版本