The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman

Spectral Clustering: Tutorial by U. von Luxburg

Spectral graph theory: Lecture Notes by D. Spielman

Empirical risk minimization: Tutorial by Boucheron, Bousquet, and Lugosi

Estimation in high dimensions: Tutorial by R. Vershynin

Compressed sensing: Tutorial by Davenport, Duarte, Eldar, and Kutyniok

Online learning: Prediction, Learning, and Games by Cesa-Bianchi and Lugosi

Gaussian processes: St. Flour lecture notes of M. Ledoux

First order methods for convex functions: Lecture notes by S. Bubeck

Stochastic approximation: Paper of Nemirovski, Juditsky, Lan, and Shapiro