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What is Combinatorial Overfitting Theory Explained about?

The document presents a combinatorial framework for analyzing overfitting in machine learning models. It discusses limitations of classical generalization bounds, which can be very loose. The proposed combinatorial approach modifies the functional form analyzed and takes a combinatorial view. Specifically, it directly bounds an empirically observable quantity of overfitting between training and testing errors, rather than probability of error. It also considers a specific learning algorithm rather than the

Author

horrlod9266

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EN