About

I am a master’s student in the Department of Computer Science at the University of British Columbia, where I am advised by Mark Schmidt. My research interests are in optimization and approximate Bayesian inference.


Recent Activities

2019

2018


Research

    Publications

    1. Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. S. Vaswani, A. Mishkin, I. Laradji, M. Schmidt, G. Gidel, S. Lacoste-Julien. NeurIPS, 2019.

    2. SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient. A. Mishkin, F. Kunstner, D. Nielsen, M. Schmidt, M. E. Khan. NeurIPS, 2018.

    3. Web ValueCharts: Analyzing Individual and Group Preferences with Interactive, Web-based Visualizations. A. Mishkin. Review of Undergraduate Computer Science, 2018.

    Slides

    1. Talks at the UBC Machine Learning Reading Group (MLRG):
    2. CUSC 2017: Web ValueCharts: Exploring Individual and Group Preferences Through Interactive Web-based Visualizations.
    3. MURC 2017: Web ValueCharts: Supporting Decision Makers with Interactive, Web-Based Visualizations

    Contact

    I can be contacted at amishkin@cs.ubc.ca and #MishkinAaron. My GitHub is aaronpmishkin.


    Aaron Mishkin