Wenda Zhou

Department of Statistics · Columbia University · New York · [email protected]

I am a Ph.D. student in statistics at Columbia University. I am interested in high-dimensional statistics, compressed sensing, and deep learning.


Research

I am interested in various topics in high-dimensional statistics, compressed sensing and deep learning.

Papers

  • Denoising Structured Random Processes ArXiv e-print

    W. Zhou, S. Jalali
  • Non-Vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach accepted at ICLR 2019

    W. Zhou, V. Veitch, M. Austern, R. P. Adams, P. Orbanz
  • Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data accepted at AISTATS 2019

    V. Veitch, M. Austern, W. Zhou, P. Orbanz, D. Blei
  • Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions ICML 2018

    S. Wang*, W. Zhou*, H. Lu, A. Maleki, V. Mirrokni
  • Analysis of Genotype by Methylation Interactions through Sparsity-Inducing Regularized Regression BMC Proceedings 2018 (GAW 20)

    W. Zhou, S. Lo

Service

I have reviewed for ICML, JMLR, ICLR, ISIT.

Education

Columbia University

Ph.D. Statistics
August 2015 - Current

Cambridge University

B.A. with MMaths (Part III)
October 2011 - May 2015

Lycée International de St Germain en Laye

Bac Scientifique Mention très bien.
October 2011

Teaching

  • Introduction to Statistics with Calculus Summer 2017

    S1201

    This is Columbia's introductory statistics class. All the material for this class (including full notes and R notebook demonstrations) are available on the github.
  • Advanced Machine Learning Fall 2017

    GR5245

    The course page for this class is available here.