Suggested Readings
There is no required reading. The curious student is invited to read the following related material.
- 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]
- Courses and Lecture Notes
- Peter Bartlett at UC Berkeley.
- Sebastien Bubeck (PDF) at Princeton.
- Sebastien Bubec (PDF) (again) at Princeton.
- Elad Hazan at Princeton.
- Gabor Lugosi at Pompeu-Babra.
- Maxim Raginsky at UIUC.
- Alexander Rakhlin at Penn.
- Shai Shalev-Shwartz (PDF) at Hebrew U.
- Dmitry Panchenko at MIT.
- Other Readings
- Three Proofs of the Sauer-Shelah Lemma (PDF) by Hung Q. Ngo.
- History of the Sauer-Shelah Lemma (PDF) by Leon Bottou.
