TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization
Code for paper "TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization". Xiang Li, Junchi Yang, Niao He.
The code for the three tasks mentioned in the paper is store in sub-directories with corresponding names.
The following packages of Python are required for running the code:
torch
torchvision
matplotlib
numpy
tensorflow
tensorboard
Pillow
scikit_learn
scipy
six
For each task, after entering the folder, simply use
bash run.sh
to run the experiments described in the paper.
To visualize the results, use tensorboard as
tensorboard --logdir logs
we used code from https://github.com/Louis-udm/Reproducing-certifiable-distributional-robustness for distributional robustness optimization experiments, and https://github.com/Zeleni9/pytorch-wgan for WGAN-GP experiments.