Contents
Preface xi
Editors xiii
Contributors xv
I General Perspectives on Big Data 1
1 The Advent of Data Science: Some Considerations
on the Unreasonable Effectiveness of Data 3
Richard J.C.M. Starmans
2Big-n versus Big-p in Big Data 21
Norman Matloff
II Data-Centric, Exploratory Methods 33
3 Divide and Recombine: Approach for Detailed Analysis
and Visualization of Large Complex Data 35
Ryan Hafen
4 Integrate Big Data for Better Operation, Control, and Protection
of Power Systems 47
Guang Lin
5 Interactive Visual Analysis of Big Data 61
Carlos Scheidegger
6 A Visualization Tool for Mining Large Correlation Tables:
The Association Navigator 73
Andreas Buja, Abba M. Krieger, and Edward I. George
III Efficient Algorithms 103
7 High-Dimensional Computational Geometry 105
Alexandr Andoni
8 IRLBA: Fast Partial Singular Value Decomposition Method 125
James Baglama
9 Structural Properties Underlying High-Quality Randomized
Numerical Linear Algebra Algorithms 137
Michael W. Mahoney and Petros Drineas
vii
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
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