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update README.md
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An Wangpeng committed Apr 10, 2018
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2 changes: 1 addition & 1 deletion README.md
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## The full code will coming out at June. :)
## PID (Present, Past and Future) Optimizer for deep learning optimization
This is the code associated with A PID Controller Approach for Stochastic Optimization of Deep Networks, CVPR 2018.
## Usage:
## Visualization:
## Citation:
If PIDOptimizer is used in your paper/experiments, please cite the following papers.
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40 changes: 20 additions & 20 deletions momentum.txt
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Learning Rate Train Loss Valid Loss Train Acc. Valid Acc.
0.010000 0.516547 0.289208 86.581667 91.600000
0.010000 0.259415 0.216152 92.545000 93.950000
0.010000 0.201986 0.177764 94.343333 94.780000
0.010000 0.165051 0.149667 95.318333 95.600000
0.010000 0.139030 0.128418 96.070000 96.220000
0.010000 0.119939 0.116352 96.710000 96.600000
0.010000 0.104811 0.104972 97.101667 96.880000
0.010000 0.093801 0.096976 97.466667 97.120000
0.010000 0.084180 0.094102 97.731667 97.140000
0.010000 0.076191 0.085866 97.956667 97.510000
0.010000 0.069832 0.081906 98.118333 97.590000
0.010000 0.064328 0.079128 98.340000 97.710000
0.010000 0.059059 0.077403 98.468333 97.740000
0.010000 0.055209 0.074700 98.570000 97.780000
0.010000 0.051301 0.072494 98.680000 97.880000
0.010000 0.047872 0.071196 98.815000 97.770000
0.010000 0.044999 0.071158 98.900000 97.790000
0.010000 0.042177 0.066217 98.998333 97.990000
0.010000 0.039857 0.066495 99.031667 97.970000
0.010000 0.037694 0.065470 99.106667 97.950000
0.010000 0.509680 0.275800 86.908333 92.210000
0.010000 0.255431 0.213543 92.813333 93.890000
0.010000 0.198463 0.172725 94.408333 95.110000
0.010000 0.162204 0.146753 95.431667 95.830000
0.010000 0.136709 0.126174 96.183333 96.420000
0.010000 0.117841 0.118981 96.771667 96.630000
0.010000 0.103934 0.104209 97.195000 96.940000
0.010000 0.092159 0.095841 97.493333 97.290000
0.010000 0.082991 0.089649 97.791667 97.350000
0.010000 0.075273 0.084053 97.988333 97.520000
0.010000 0.069048 0.082308 98.156667 97.550000
0.010000 0.063580 0.077542 98.346667 97.710000
0.010000 0.058794 0.075400 98.473333 97.730000
0.010000 0.054611 0.072476 98.615000 97.790000
0.010000 0.050820 0.071925 98.718333 97.820000
0.010000 0.047619 0.069473 98.765000 97.920000
0.010000 0.044399 0.067499 98.933333 98.040000
0.010000 0.041778 0.067148 98.973333 98.000000
0.010000 0.039280 0.065606 99.058333 98.030000
0.010000 0.037374 0.065613 99.118333 97.950000
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