Readings

Suggested Readings

There is no required reading. The curious student is invited to read the following related material.

  1. Books
    • Bubeck, Sebastien, and Nicolo Cesa-Bianchi. Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems. Now Publishers Incorporate, 2012. ISBN: 9781601986269.
    • Cesa-Bianchi, Nicolo, and Gabor Lugosi. Prediction, Learning, and Games. Cambridge University Press, 2006. ISBN: 9780521841085. [Preview with Google Books]
    • Giraud, Christophe. Introduction to High-Dimensional Statistics. Chapman and Hall / CRC, 2014. ISBN: 9781482237948.
    • Koltchinskii, Vladimir. Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d’Été de Probabilités de Saint-Flour XXXVIII–2008. Springer, 2011. ISBN: 9783642221460. [Preview with Google Books]
    • Shalev-Shwartz, Shai, and Shai Ben-David. Understanding Machine Learning: From Theory to Algorithms. Cambridge University Press, 2014. ISBN: 9781107057135. [Preview with Google Books]
  2. Courses and Lecture Notes
  3. Other Readings

Course Info

Learning Resource Types

notes Lecture Notes
assignment_turned_in Problem Sets with Solutions