• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 26 matches

• 2016
• 
  Alexandr Andoni:
  High-Dimensional Computational Geometry. Handbook of Big Data 2016: 105-123
• 
  James Baglama:
  IRLBA: Fast Partial Singular Value Decomposition Method. Handbook of Big Data 2016: 125-136
• 
  Laura Balzer, Maya Petersen, Mark J. van der Laan:
  Tutorial for Causal Inference. Handbook of Big Data 2016: 361-386
• 
  Jacob Bien, Daniela M. Witten:
  Penalized Estimation in Complex Models. Handbook of Big Data 2016: 285-303
• 
  Andreas Buja, Abba M. Krieger, Edward I. George:
  A Visualization Tool for Mining Large Correlation Tables: The Association Navigator. Handbook of Big Data 2016: 73-102
• 
  Ilias Diakonikolas:
  Learning Structured Distributions. Handbook of Big Data 2016: 267-283
• 
  Iván Díaz:
  Estimator and Model Selection Using Cross-Validation. Handbook of Big Data 2016: 223-239
• 
  David F. Gleich, Michael W. Mahoney:
  Mining Large Graphs. Handbook of Big Data 2016: 191-220
• 
  Ryan Hafen:
  Divide and Recombine: Approach for Detailed Analysis and Visualization of Large Complex Data. Handbook of Big Data 2016: 35-46
• 
  Alan E. Hubbard, Mark J. van der Laan:
  Mining with Inference: Data-Adaptive Target Parameters. Handbook of Big Data 2016: 439-452
• 
  Erin LeDell:
  Scalable Super Learning. Handbook of Big Data 2016: 339-357
• 
  Sam Lendle:
  Online Estimation of the Average Treatment Effect. Handbook of Big Data 2016: 429-438
• 
  Guang Lin:
  Integrate Big Data for Better Operation, Control, and Protection of Power Systems. Handbook of Big Data 2016: 47-60
• 
  Marloes H. Maathuis, Preetam Nandy:
  A Review of Some Recent Advances in Causal Inference. Handbook of Big Data 2016: 387-407
• 
  Michael W. Mahoney, Petros Drineas:
  Structural Properties Underlying High-Quality Randomized Numerical Linear Algebra Algorithms. Handbook of Big Data 2016: 137-154
• 
  Norman S. Matloff:
  Big-n versus Big-p in Big Data. Handbook of Big Data 2016: 21-32
• 
  Lukas Meier:
  High-Dimensional Regression and Inference. Handbook of Big Data 2016: 305-319
• 
  Elizabeth L. Ogburn, Alexander Volfovsky:
  Networks. Handbook of Big Data 2016: 171-190
• 
  Sherri Rose:
  Targeted Learning for Variable Importance. Handbook of Big Data 2016: 411-427
• 
  Ronitt Rubinfeld, Eric Blais:
  Something for (Almost) Nothing: New Advances in Sublinear-Time Algorithms. Handbook of Big Data 2016: 155-167
• 
  Stephanie Sapp, Erin LeDell:
  Divide and Recombine: Subsemble, Exploiting the Power of Cross-Validation. Handbook of Big Data 2016: 323-338
• 
  Carlos Scheidegger:
  Interactive Visual Analysis of Big Data. Handbook of Big Data 2016: 61-71
• 
  Richard J. C. M. Starmans:
  The Advent of Data Science: Some Considerations on the Unreasonable Effectiveness of Data. Handbook of Big Data 2016: 3-19
• 
  Panos Toulis, Edoardo M. Airoldi:
  Stochastic Gradient Methods for Principled Estimation with Large Datasets. Handbook of Big Data 2016: 241-265
• 
  Index. Handbook of Big Data 2016: 453-464
• 
  Peter Bühlmann, Petros Drineas, Michael J. Kane, Mark J. van der Laan:
  Handbook of Big Data. Chapman and Hall/CRC 2016, ISBN 978-1-4822-4907-1 [contents]