Skip to main content
Cornell university
Cornell Statistics and Data Science Cornell Statistics and Data Science
  • About Us

    About Us
    Cornell's Department of Statistics and Data Science offers four programs at the undergraduate and graduate levels. Undergraduates can earn a BA in statistical science, social...

    Welcome to the Department of Statistics and Data Science
    History
    Facilities
    Statistics Graduate Society
    Recently Published Papers
  • Academics

    Academics

    Undergraduate
    PhD
    MPS
    PhD Minor in Data Science
    Courses & Course Enrollment
  • People

    People

    Faculty
    Field Faculty
    PhDs
    Emeritus Faculty
    Academic Staff
    Staff
    Research Areas of Expertise
    Statistical Consultants
  • News and Events

    News and Events

    Events
    News
  • Resources

    Resources

    Professional Societies and Meetings
    Affiliated Groups
    Career Services
    Cornell Statistical Consulting Unit
  • Alumni

    Alumni
    Cornell's Statistics and Data Science degrees prepare students for a wide variety of careers, from academia to industry.  See the After Graduation page for a general overview of...

    Alumni Profiles

Search form

You are here

  1. Home 
  2. Events 
  3. Statistics Seminars

Statistics Seminar Speaker Johannes Lederer, 1/20/15

Event Layout

Tuesday Jan 20 2015

Statistics Seminar Speaker Johannes Lederer, 1/20/15

11:00am @ G01 Biotechnology
In Statistics Seminars

The Statistics Seminar speaker for Jan. 20, 2015 will be Johannes Lederer, from Cornell University. 

Title: Tuning Parameters in High-Dimensional Statistics

Abstract: High-dimensional statistics is the basis for analyzing large and complex data sets that are generated by cutting-edge technologies in genetics, neuroscience, astronomy, and many other fields. However, Lasso, Ridge Regression, Graphical Lasso, and other standard methods in high-dimensional statistics depend on tuning parameters that are difficult to calibrate in practice. In this talk, I present two novel approaches to overcome this difficulty. My first approach is based on a novel testing scheme that is inspired by Lepski’s idea for bandwidth selection in non-parametric statistics. This approach provides tuning parameter calibration for estimation and prediction with the Lasso and other standard methods and is to date the only way to ensure high performance, fast computations, and optimal finite sample guarantees. My second approach is based on the minimization of an objective function that avoids tuning parameters altogether. This approach provides accurate variable selection in regression settings and, additionally, opens up new possibilities for the estimation of gene regulation networks, microbial ecosystems, and many other network structures.

Event Categories

  • Statistics Seminars
  • Special Events
  • Home
  • About Us
  • Contact Us
  • Careers
© Cornell University Department of Statistics and Data Science

1198 Comstock Hall, 129 Garden Ave., Ithaca, NY 14853

Social Menu

  • Facebook
  • Twitter
  • YouTube
Cornell Bowers CIS College of Computing and Information Science Cornell CALS ILR School

If you have a disability and are having trouble accessing information on this website or need materials in an alternate format, contact web-accessibility@cornell.edu for assistance.