Shai Shalev-Shwartz Books
Shai Shalev-Shwartz is a professor at the Hebrew University of Jerusalem specializing in machine learning and optimization.
Known for: Understanding Machine Learning: From Theory to Algorithms
Books by Shai Shalev-Shwartz
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 Shalev-Shwartz
Shai Shalev-Shwartz is a professor at the Hebrew University of Jerusalem specializing in machine learning and optimization.
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Shai Shalev-Shwartz is a professor at the Hebrew University of Jerusalem specializing in machine learning and optimization.
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