viii Contents
10 Something for (Almost) Nothing: New Advances in
Sublinear-Time Algorithms 155
Ronitt Rubinfeld and Eric Blais
IV Graph Approaches 169
11 Networks 171
Elizabeth L. Ogburn and Alexander Volfovsky
12 Mining Large Graphs 191
David F. Gleich and Michael W. Mahoney
V Model Fitting and Regularization 221
13 Estimator and Model Selection Using Cross-Validation 223
Iv´an D´ıaz
14 Stochastic Gradient Methods for Principled Estimation with
Large Datasets 241
Panos Toulis and Edoardo M. Airoldi
15 Learning Structured Distributions 267
Ilias Diakonikolas
16 Penalized Estimation in Complex Models 285
Jacob Bien and Daniela Witten
17 High-Dimensional Regression and Inference 305
Lukas Meier
VI Ensemble Methods 321
18 Divide and Recombine: Subsemble, Exploiting the Power
of Cross-Validation 323
Stephanie Sapp and Erin LeDell
19 Scalable Super Learning 339
Erin LeDell
VII Causal Inference 359
20 Tutorial for Causal Inference 361
Laura Balzer, Maya Petersen, and Mark van der Laan
21 A Review of Some Recent Advances in Causal Inference 387
Marloes H. Maathuis and Preetam Nandy
VIII Targeted Learning 409
22 Targeted Learning for Variable Importance 411
Sherri Rose