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xiii41 Statistical model building, machine learning, and the ah-hamoment 481Grace Wahba41.1 Introduction: Manny Parzen and RKHS . . . . . . . . . . . . 48141.2 Regularization methods, RKHS and sparse models . . . . . . 49041.3 Remarks on the nature-nurture debate, personalized medicineand scientific literacy . . . . . . . . . . . . . . . . . . . . . . 49141.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49242 In praise of sparsity and convexity 497Robert J. Tibshirani42.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 49742.2 Sparsity, convexity and l 1 penalties . . . . . . . . . . . . . . 49842.3 An example . . . . . . . . . . . . . . . . . . . . . . . . . . . 50042.4 The covariance test . . . . . . . . . . . . . . . . . . . . . . . 50042.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50343 Features of Big Data and sparsest solution in high confidenceset 507Jianqing Fan43.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 50743.2 Heterogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . 50843.3 Computation . . . . . . . . . . . . . . . . . . . . . . . . . . . 50943.4 Spurious correlation . . . . . . . . . . . . . . . . . . . . . . . 51043.5 Incidental endogeneity . . . . . . . . . . . . . . . . . . . . . . 51243.6 Noise accumulation . . . . . . . . . . . . . . . . . . . . . . . 51543.7 Sparsest solution in high confidence set . . . . . . . . . . . . 51643.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52144 Rise of the machines 525Larry A. Wasserman44.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 52544.2 The conference culture . . . . . . . . . . . . . . . . . . . . . 52644.3 Neglected research areas . . . . . . . . . . . . . . . . . . . . 52744.4 Case studies . . . . . . . . . . . . . . . . . . . . . . . . . . . 52744.5 Computational thinking . . . . . . . . . . . . . . . . . . . . . 53344.6 The evolving meaning of data . . . . . . . . . . . . . . . . . 53444.7 Education and hiring . . . . . . . . . . . . . . . . . . . . . . 53544.8 If you can’t beat them, join them . . . . . . . . . . . . . . . 53545 A trio of inference problems that could win you a Nobel Prizein statistics (if you help fund it) 537Xiao-Li Meng45.1 Nobel Prize? Why not COPSS? . . . . . . . . . . . . . . . . 53745.2 Multi-resolution inference . . . . . . . . . . . . . . . . . . . . 539