Yeming Wen

I am a first-year graduate student in Machine Learning Group at the University of Toronto and Vector Institute, studying under Jimmy Ba and Roger Grosse. I recieved my bachelors at the University of Toronto in 2017.

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Research

My research interests focus on the development of efficient learning algorithms for deep neural networks. In particular, how to properly regularize deep neural networks such that it can continuously learn a number of tasks and generalize better.

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches
Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger Grosse,
6th International Conference on Learning Representations (ICLR), 2018

How to efficiently make psedo-independent weight perturbations on mini-batches in evolution strategies and variational BNNs as activation perturbations in dropout.


Last Update: June, 16th, 2018;
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