Past Events

  • 2013 Nov 06

    MachineLearn: Tamara Broderick

    4:00pm to 5:00pm

    Location: 

    Maxwell-Dworkin G125
    Feature allocations, probability functions, and paintboxes The problem of inferring a clustering of a data set has been the subject of much research in Bayesian analysis, and there currently exists a solid mathematical foundation for Bayesian approaches to clustering. In particular, the class of probability distributions over partitions of a data set has been characterized in a number of ways, including via exchangeable partition probability functions (EPPFs) and the Kingman paintbox. Here, we develop a generalization of the clustering problem, called feature allocation, where we allow each... Read more about MachineLearn: Tamara Broderick
  • 2013 Nov 06

    ApplStatWksp: Amy Sliva

    12:00pm to 1:30pm

    Location: 

    CGIS Knafel K354
    Scalable Analysis of Behavioral Models and Decision-Making
  • 2013 Nov 04

    BrownCSSem: Hongtu Zhu

    3:30pm to 5:00pm

    Location: 

    Room 245, 121 South Main Street, Providence
    Spatial and Adaptive Models for Neuroimaging Data
  • 2013 Oct 31

    MIT ORC: Alex Belloni

    4:15pm to 5:30pm

    Location: 

    E51-335
    Uniform Inference After Model Selection
  • 2013 Oct 31

    HSPHBiostat: Jesse Berlin

    1:30pm to 3:30pm

    Location: 

    FXB G13
    [Lagakos Distinguished Alumni Award] Perspectives of a Recovering Academic Biostatistician: Transitions and Lessons Learned about Statistics and Beyond
  • 2013 Oct 30

    Future of Statistics Unconference

    12:00pm to 1:00pm

    Location: 

    Google Hangouts & YouTube
    There will be 10 minute talks on a wide variety of future directions in statistics by Hadley Wickham (Chief Scientist at RStudio and creator of ggplot2), Hongkai Ji (Johns Hopkins professor and Harvard Stat alumnus), Sinan Aral (MIT), Daniela Witten (Univ of Washington), Hilary Mason (Data Scientist in Residence at Accel & co-founder of HackNY) and Joe Blitzstein (Harvard Stat professor). Here is more publicity.

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