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]

Email: sridharan at cs dot cornell dot edu