Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical

part I|2 pages

General Perspectives on Big Data

chapter 2|12 pages

Big-n versus Big-p in Big Data

ByNorman Matloff

part II|2 pages

Data-Centric, Exploratory Methods

chapter 5|12 pages

Interactive Visual Analysis of Big Data

ByCarlos Scheidegger

chapter 6|30 pages

A Visualization Tool for Mining Large Correlation Tables: The Association Navigator

ByAndreas Buja, Abba M. Krieger, Edward I. George

part III|2 pages

Efficient Algorithms

chapter 7|20 pages

High-Dimensional Computational Geometry

ByAlexandr Andoni

chapter 8|12 pages

IRLBA: Fast Partial Singular Value Decomposition Method

ByJames Baglama

chapter 9|18 pages

Structural Properties Underlying High-Quality Randomized Numerical Linear Algebra Algorithms

ByMichael W. Mahoney, Petros Drineas

chapter 10|14 pages

Something for (Almost) Nothing: New Advances in Sublinear-Time Algorithms

ByRonitt Rubinfeld, Eric Blais

part IV|2 pages

Graph Approaches

chapter 11|20 pages


ByElizabeth L. Ogburn, Alexander Volfovsky

chapter 12|30 pages

Mining Large Graphs

ByDavid F. Gleich, Michael W. Mahoney

part V|2 pages

Model Fitting and Regularization

chapter 14|26 pages

Stochastic Gradient Methods for Principled Estimation with Large Datasets

ByPanos Toulis, Edoardo M. Airoldi

chapter 16|20 pages

Penalized Estimation in Complex Models

ByJacob Bien, Daniela Witten

chapter 17|16 pages

High-Dimensional Regression and Inference

ByLukas Meier

part VI|2 pages

Ensemble Methods

chapter 18|16 pages

Divide and Recombine: Subsemble, Exploiting the Power of Cross-Validation

ByStephanie Sapp and Erin LeDell

chapter 19|20 pages

Scalable Super Learning Erin LeDell

part VII|2 pages

Causal Inference

chapter 20|26 pages

Tutorial for Causal Inference

ByLaura Balzer, Maya Petersen, Mark van der Laan

chapter 21|22 pages

A Review of Some Recent Advances in Causal Inference

ByMarloes H. Maathuis, Preetam Nandy

part VIII|2 pages

Targeted Learning

chapter 22|18 pages

Targeted Learning for Variable Importance

BySherri Rose

chapter 23|10 pages

Online Estimation of the Average Treatment Effect

BySam Lendle

chapter 24|14 pages

Mining with Inference: Data-Adaptive Target Parameters

ByAlan Hubbard, Mark van der Laan