JSM2013

This post is for JSM2013. I will put useful links here and I will update this post during the meeting.

1. Big Data Sessions at JSM
2. Nate Silver addresses assembled statisticians at this year’s JSM
3. Data scientist is just a sexed up word for statistician

What I have learned from this meeting (Key words of this meeting):

Big Data, Bayesian, Statistical Efficiency vs Computational Efficiency

I was in Montreal from Aug 1st to Aug 8th for JSM2013 and traveling.

(Traveling in Quebec: Olympic Stadium; Underground City; Quebec City; Montreal City; basilique Nortre-Dame; China Town)

(Talks at JSM2013: Jianqing Fan; Jim Berger; Nate Silver; Tony Cai; Han Liu; Two Statistical Peters)

(My Presentation at JSM2013)

The following is the list for the talks I was there:

JSM

• Aug 4th
  • 2:05 PM Analyzing Large Data with R and MonetDB — Thomas Lumley, University of Auckland
  • 2:25 PM Empirical Likelihood and U-Statistics in Survival Analysis — Zhigang Zhang, Memorial Sloan-Kettering Cancer Center ; Yichuan Zhao, Georgia State University
  • 2:50 PM Joint Unified Confidence Region for the Parameters of Branching Processes with Immigration — Pin Ren ; Anand Vidyashankar, George Mason University
  • 3:05 PM Time-Varying Additive Models for Longitudinal Data — Xiaoke Zhang, University of California Davis ; Byeong U. Park, Seoul National University ; Jane-Ling Wang, UC Davis
  • 3:20 PM Leveraging as a Paradigm for Statistically Informed Large-Scale Computation — Michael W. Mahoney, Stanford University
  • 4:05 PM Joint Estimation of Multiple Dependent Gaussian Graphical Models — Yuying Xie, The University of North Carolina at Chapel Hill ; Yufeng Liu, The University of North Carolina ; William Valdar, UNC-CH Genetics
  • 4:30 PM Computational Strategies in Regression of Big Data — Ping Ma, University of Illinois at Urbana-Champaign
  • 4:55 PM Programming with Big Data in R — George Ostrouchov, Oak Ridge National Laboratory ; Wei-Chen Chen, Oak Ridge National Laboratory ; Drew Schmidt, University of Tennessee ; Pragneshkumar Patel, University of Tennessee
  • 5:20 PM Inference and Optimalities in Estimation of Gaussian Graphical Model — Harrison Zhou, Yale University
• Aug 5th
  • 99 Mon, 8/5/2013, 8:30 AM – 10:20 AM CC-710a
    • Introductory Overview Lecture: Twenty Years of Gibbs Sampling/MCMC — Other Special Presentation
    • 8:35 AM Gibbs Sampling and Markov Chain Monte Carlo: A Modeler’s Perspective — Alan E. Gelfand, Duke University
    • 9:25 AM The Theoretical Underpinnings of MCMC — Jeffrey S. Rosenthal, University of Toronto
    • 10:15 AM Floor Discussion
  • 166 * Mon, 8/5/2013, 10:30 AM – 12:20 PM CC-520c
    • Statistical Learning and Data Mining: Winners of Student Paper Competition — Topic Contributed Papers
    • 10:35 AM Multicategory Angle-Based Large Margin Classification — Chong Zhang, UNC-CH ; Yufeng Liu, The University of North Carolina
    • 10:55 AM Discrepancy Pursuit: A Nonparametric Framework for High-Dimensional Variable Selection — Li Liu, Carnegie Mellon University ; Kathryn Roeder, CMU ; Han Liu, Princeton University
    • 11:15 AM PenPC: A Two-Step Approach to Estimate the Skeletons of High-Dimensional Directed Acyclic Graphs — Min Jin Ha ; Wei Sun, UNC Chapel Hill ; Jichun Xie, Temple University
    • 11:35 AM An Underdetermined Peaceman-Rachford Splitting Algorithm with Application to Highly Nonsmooth Sparse Learning Problems— Zhaoran Wang, Princeton University ; Han Liu, Princeton University ; Xiaoming Yuan, Hong Kong Baptist University
    • 11:55 AM Latent Supervised Learning — Susan Wei, UNC
    • 12:15 PM Floor Discussion
  • 220 Mon, 8/5/2013, 2:00 PM – 3:50 PM CC-710b
    • 2:05 PM Statistics Meets Computation: Efficiency Trade-Offs in High Dimensions — Martin Wainwright, UC Berkeley
    • 3:35 PM Floor Discussion
  • 267 Mon, 8/5/2013, 4:00 PM – 5:50 PM CC-517ab
    • 4:05 PM JSM Welcomes Nate Silver — Nate Silver, FiveThirtyEight.com
  • 209305 Mon, 8/5/2013, 6:00 PM – 8:00 PM I-Maisonneuve, JSM Student Mixer, Sponsored by Pfizer — Other Cmte/Business, ASA , Pfizer, Inc.
  • 268 Mon, 8/5/2013, 8:00 PM – 9:30 PM CC-517ab
    • 8:05 PM Ars Conjectandi: 300 Years Later — Hans Rudolf Kunsch, Seminar fur Statistik, ETH Zurich
• Aug 6th
  • 280 * Tue, 8/6/2013, 8:30 AM – 10:20 AM CC-510a
    • Statistical Inference for Large Matrices — Invited Papers
    • 8:35 AM Conditional Sparsity in Large Covariance Matrix Estimation — Jianqing Fan, Princeton University ; Yuan Liao, University of Maryland ; Martina Mincheva, Princeton University
    • 9:05 AM Multivariate Regression with Calibration — Lie Wang, Massachusetts Institute of Technology ; Han Liu, Princeton University ; Tuo Zhao, Johns Hopkins University
    • 9:35 AM Principal Component Analysis for High-Dimensional Non-Gaussian Data — Fang Han, Johns Hopkins University ; Han Liu, Princeton University
    • 10:05 AM Floor Discussion
  • 325 * ! Tue, 8/6/2013, 10:30 AM – 12:20 PM CC-520b
    • Modern Nonparametric and High-Dimensional Statistics — Invited Papers
    • 10:35 AM Simple Tiered Classifiers — Peter Gavin Hall, University of Melbourne ; Jinghao Xue, University College London ; Yingcun Xia, National University of Singapore
    • 11:05 AM Sparse PCA: Optimal Rates and Adaptive Estimation — Tony Cai, University of Pennsylvania
    • 11:35 AM Statistical Inference in Compound Functional Models — Alexandre Tsybakov, CREST-ENSAE
    • 12:05 PM Floor Discussion
  • 392 Tue, 8/6/2013, 2:00 PM – 3:50 PM CC-710a
    • Introductory Overview Lecture: Big Data — Other Special Presentation
    • 2:05 PM The Relative Size of Big Data — Bin Yu, Univ of California at Berkeley
    • 2:55 PM Divide and Recombine (D&R) with RHIPE for Large Complex Data — William S. Cleveland, Purdue Universith
    • 3:45 PM Floor Discussion
  • 445 Tue, 8/6/2013, 4:00 PM – 5:50 PM CC-517ab
    • Deming Lecture — Invited Papers
    • 4:05 PM Industrial Statistics: Research vs. Practice — Vijay Nair, University of Michigan
• Aug 7th
  • 10:35 AM Bayesian and Frequentist Issues in Large-Scale Inference — Bradley Efron, Stanford University
  • 11:20 AM Criteria for Bayesian Model Choice with Application to Variable Selection — Jim Berger, Duke University ; Susie Bayarri, University of Valencia ; Anabel Forte, Universitat Jaume I ; Gonzalo Garcia-Donato, Universidad de Castilla-La Mancha
  • 571 Wed, 8/7/2013, 2:00 PM – 3:50 PM CC-511c
    • Statistical Methods for High-Dimensional Sequence Data — Invited Papers
    • 2:05 PM Linkage Disequilibrium in Sequencing Data: A Blessing or a Curse? — Alkes L. Price, Harvard School of Public Health
    • 2:25 PM Statistical Prioritization of Sequence Variants — Lisa Joanna Strug, The Hospital for Sick Children and University of Toronto ; Weili Li, The Hospital for Sick Children and University of Toronto
    • 2:45 PM On Some Statistical Issues in Analyzing Whole-Genome Sequencing Data — Dan Liviu Nicolae, The University of Chicago
    • 3:05 PM Statistical Methods for Studying Rare Variant Effects in Next-Generation Sequencing Association Studies — Xihong Lin, Harvard School of Public Health
    • 3:25 PM Adjustment for Population Stratification in Association Analysis of Rare Variants — Wei Pan, University of Minnesota ; Yiwei Zhang, University of Minnesota ; Binghui Liu, University of Minnesota ; Xiaotong Shen, University of Minnesota
    • 3:45 PM Floor Discussion
  • 612 Wed, 8/7/2013, 4:00 PM – 5:50 PM CC-517ab
    • COPSS Awards and Fisher Lecture — Invited Papers
    • 4:05 PM From Fisher to Big Data: Continuities and Discontinuities — Peter Bickel, University of California – Berkeley
    • 5:45 PM Floor Discussion
• Aug 8th
  • 621 Thu, 8/8/2013, 8:30 AM – 10:20 AM CC-516d
    • Recent Advances in Bayesian Computation — Invited Papers
    • 8:35 AM An Adaptive Exchange Algorithm for Sampling from Distribution with Intractable Normalizing Constants — Faming Liang, Texas A&M University
    • 9:00 AM Efficiency of Markov Chain Monte Carlo for Bayesian Computation — Dawn B Woodard, Cornell University
    • 9:25 AM Scalable Inference for Hierarchical Topic Models — John W. Paisley, University of California, Berkeley
    • 9:50 AM Augmented Particle Filters — Yuguo Chen, University of Illinois at Urbana-Champaign
    • 10:15 AM Floor Discussion
  • 661 * ! Thu, 8/8/2013, 10:30 AM – 12:20 PM CC-710b
    • Patterns and Extremes: Developments and Review of Spatial Data Analysis — Invited Papers
    • 10:35 AM Multivariate Max-Stable Spatial Processes — Marc G. Genton, KAUST ; Simone Padoan, Bocconi University of Milan ; Huiyan Sang, TAMU
    • 10:55 AM Approximate Bayesian Computing for Spatial Extremes — Robert James Erhardt, Wake Forest University ; Richard Smith, The University of North Carolina at Chapel Hill