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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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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