Mark Schmidt

  Mark Schmidt
    Department of Computer Science
    University of British Columbia
    201 2366 Main Mall
    Vancouver BC V6T 1Z4

Frequently-Answered E-mails (regarding supervision, courses, internships, collaborations, etc.)

Seeking postdoctoral researchers focusing on optimization and generalization in deep learning


  • List of Publications - with links to code, presentations/posters, and appendices.

    Selected recent papers on optimization for machine learning: Selected recent papers on probabilistic machine learning: Selected computer vision applications: Other selected applications: PhD thesis (2010): Graphical Model Structure Learning with L1-Regularization


    Talk slides on selected recent projects related to optimization for machine learning: Overview talk slides: Selected recent posters related to optimization for machine learning: Recent videos of talks by myself and co-authors related to optimization for machine learning:


  • List of Software Packages

    Some Highlights: A package containing most of the above is available here.

    Teaching and Research Groups

  • 100 Lectures on Machine Learning - material from all my courses in one place.

    UBC Courses:

    Mini-Courses: Tutorials: My Lab (Summer 2020):

    UBC Machine Learning Lab

    Current members:


    UBC Machine Learning Reading Group

    Selected Notes

    List of Notes

    Cauchy's original paper from 1847 on gradient descent is available here.

    I've also been known to swim, spike, and dunk.