Reference Material :

1. Understanding Machine Learning From Theory to Algorithms, S. Ben David and S. Shalev-Shwartz [link]

2. Foundations of Machine Learning, Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar [link]

3. Introduction to Statistical Learning Theory, O. Bousquet, S. Boucheron, and G. Lugosi [pdf]

4. Prediction Learning and Games, N. Cesa-Bianchi and G. Lugosi [link]

5. Statistical Learning and Sequential Prediction, A. Rakhlin and K. Sridharan [pdf]

6. Introduction to Online Convex Optimization, Elad Hazan [link]

7. Concentration inequalities, S. Boucheron, O. Bousquet, and G. Lugosi [pdf]

8. A Gentle Introduction to Concentration Inequalities, K. Sridharan [pdf]

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