tangmhmhmh/PIDOptimizer

Code for this CVPR 2018 paper: "A PID Controller Approach for Stochastic Optimization of Deep Networks", Wangpeng An, Haoqian Wang, Qingyun Sun, Jun Xu, Qionghai Dai, Lei Zhang.

Python

PIDOptimizer (Proportional–Integral–Derivative Optimizer)

This repository contains source code of the CVPR 2018 paper:

A PID Controller Approach for Stochastic Optimization of Deep Networks, Wangpeng An, Haoqian Wang, Qingyun Sun, Jun Xu, Qionghai Dai, Lei Zhang.

Prerequisite:

matplotlib==2.0.2

Train MLP on MNIST DATAST

python mnist_pid.py python mnist_momentum.py python compare.py

PID Vs. SGD-Momentum

Citation:

If PIDOptimizer is used in your paper/experiments, please cite the following paper.

@InProceedings{An_2018_CVPR,
author = {An, Wangpeng and Wang, Haoqian and Sun, Qingyun and Xu, Jun and Dai, Qionghai and Zhang, Lei},
title = {A PID Controller Approach for Stochastic Optimization of Deep Networks},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}