Four papers at top machine learning conference

Published April 25, 2016

CSE will present four papers at the 33rd International Conference on Machine Learning (ICML 2016)  in NYC in June. The ICML program committee accepted only 322 of 1,327 submissions.

Our papers are:

  • "Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing", Marco Gaboardi, Hyun woo Lim, Ryan Rogers, Salil Vadhan.
  • "Network Morphism", Tao Wei, Chang Wen Chen.
  • "Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks", Devansh Arpit, Yingbo Zhou, Bhargava U. Kota, Venu Govindaraju.
  • "Why Regularized Auto-Encoders learn Sparse Representation?", Devansh Arpit, Yingbo Zhou, Hung Ngo, Venu Govindaraju.