Gabriel Huang (he/him)
PhD, Mila & University of Montreal
Research Scientist, ServiceNow
Below is an interactive visualization of our paper Negative Momentum for
Improved Game Dynamics:
(a) Learning rate (lr) and momentum (beta) hyperparameters.
(b) Resulting eigenvalues in the complex plane for SGD and SGD+momentum.
There is convergence if and only if all eigenvalues are inside the convergence ball (green).
Try to find the
hyperparameters for convergence.
SGD without momentum: using ,
eigenvalues are the convergence ball →
SGD with momentum: using
and momentum ,
eigenvalues are the convergence ball →
The Thin-8 dataset consists of 1585 grayscale handwritten images of the digit 8, with resolution
512x512.
16 people were asked to draw the digit 8 about 100 times using a pen on a tablet PC running Microsoft Windows.
It was collected in October 2017 at the University of Montreal.
Download Thin-8 dataset here
If you use the Thin-8 dataset, please cite our paper :
@article{huang2018parametric,
title={Parametric Adversarial Divergences are Good Task Losses for Generative Modeling},
author={Huang, Gabriel and Berard, Hugo and Touati, Ahmed and Gidel, Gauthier and Vincent, Pascal and Lacoste-Julien, Simon},
journal={arXiv preprint arXiv:1708.02511},
year={2017}
}
Thanks to Alex, Akram, Aristide, David, Dendi, Eugene, Jae, Joao, Liam, Rémi, Rosemary, Shawn, Sina, and Xing for scribbling all those samples!
Email: gbxhuang@gmail.com
In person: Mila, 6666 St-Urbain, #200, Montreal, QC, H2S 3H1, Canada