Shai Ben-David Books
Shai Ben-David is a professor at the University of Waterloo known for his contributions to theoretical computer science and learning theory.
Known for: Understanding Machine Learning: From Theory to Algorithms
Books by Shai Ben-David
Understanding Machine Learning: From Theory to Algorithms
This book provides a comprehensive introduction to the theoretical foundations of machine learning. It covers fundamental concepts such as PAC learning, VC dimension, boosting, kernel methods, and online learning. The authors present rigorous mathematical formulations alongside intuitive explanations, making it suitable for advanced undergraduate and graduate students in computer science and related fields.
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Formalizing the Learning Problem: The PAC Framework
At the start of our exploration, we realized the term 'learning' needed precision. Informally, we say an algorithm learns when it improves through experience. Formally, we define learning in the framework introduced by Valiant—the Probably Approximately Correct (PAC) model. The PAC framework gives u...
From Understanding Machine Learning: From Theory to Algorithms
Sample Complexity, Generalization, and Hypothesis Spaces
Once the PAC model sets the stage, we must ask what controls the learner’s ability to generalize from finite samples. A central insight of learning theory is that generalization does not depend solely on the amount of data but on the capacity of the hypothesis space. The hypothesis space represents ...
From Understanding Machine Learning: From Theory to Algorithms
About Shai Ben-David
Shai Ben-David is a professor at the University of Waterloo known for his contributions to theoretical computer science and learning theory.
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Shai Ben-David is a professor at the University of Waterloo known for his contributions to theoretical computer science and learning theory.
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