A First Principles Theory of Generalization
Some new research from University of California, Berkeley shades some new light into how to quantify neural networks knowledge.
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Most of machine learning(ML) papers we see these days are focused on advancing new techniques and methods in different areas such as natural language or computer vision. ML research is advancing at a frantic pace despite the lack of fundamental theory of machine intelligence. Some of the main questions in ML such as how to understand how neural networks learn or how to quantify knowledge generalization remain unanswered. From time to time, we come across papers that are challenging our fundamental understanding of ML theory with new…
