Content: GENERAL PERSPECTIVES ON BIG DATAThe Advent of Data Science: Some Considerations on the Unreasonable Effectiveness of DataRichard StarmansBig n versus Big p in Big DataNorman MatloffDATA-CENTRIC, EXPLORATORY METHODSDivide and Recombine: Approach for Detailed Analysis and Visualization of Large Complex DataRyan HafenIntegrate Big Data for Better Operation, Control, and Protection of Power SystemsGuang LinInteractive Visual Analysis of Big DataCarlos ScheideggerA Visualization Tool for Mining Large Correlation Tables: The Association NavigatorAndreas Buja, Abba M. Krieger, and Edward I. GeorgeEFFICIENT ALGORITHMSHigh-Dimensional Computational GeometryAlexandr AndoniIRLBA: Fast Partial SVD MethodJames BaglamaStructural Properties Underlying High-Quality Randomized Numerical Linear Algebra AlgorithmsMichael W. Mahoney and Petros DrineasSomething for (Almost) Nothing: New Advances in Sublinear-Time AlgorithmsRonitt Rubinfeld and Eric BlaisGRAPH APPROACHESNetworksElizabeth L. Ogburn and Alexander VolfovskyMining Large GraphsDavid F. Gleich and Michael W. MahoneyMODEL FITTING AND REGULARIZATIONEstimator and Model Selection Using Cross-ValidationIvan DiazStochastic Gradient Methods for Principled Estimation with Large DatasetsPanos Toulis and Edoardo M. AiroldiLearning Structured DistributionsIlias DiakonikolasPenalized Estimation in Complex ModelsJacob Bien and Daniela WittenHigh-Dimensional Regression and InferenceLukas MeierENSEMBLE METHODSDivide and Recombine Subsemble, Exploiting the Power of Cross-ValidationStephanie Sapp and Erin LeDellScalable Super LearningErin LeDellCAUSAL INFERENCETutorial for Causal InferenceLaura Balzer, Maya Petersen, and Mark van der LaanA Review of Some Recent Advances in Causal InferenceMarloes H. Maathuis and Preetam NandyTARGETED LEARNINGTargeted Learning for Variable ImportanceSherri RoseOnline Estimation of the Average Treatment EffectSam LendleMining with Inference: Data-Adaptive Target ParametersAlan Hubbard and Mark van der Laan