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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.

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Jul 27, 2018
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Jul 27, 2018

PIDOptimizer (Proportional–Integral–Derivative Optimizer)

This repository contains source code of the CVPR 2018 paper:

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}
}

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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.

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