Lipschitz Adaptive Learning Rate

This is an implemetation of paper by:-
Yedida, Rahul, and Snehanshu Saha. "A novel adaptive learning rate scheduler for deep neural networks." arXiv preprint arXiv:1902.07399 (2019).
Using keras and Tensorflow . Main function is lr_scheduler which uses the callback of LRScheduler. All the code can be found in this repository.
The research paper that has been implemented is also uploaded
The summary sheet is made which contains the result for all of the datasets.
The datasets on which this LALR is implemented are:-

• MNIST
• IRIS
• Boston Housing data
• CIFAR-10
• CIFAR-100

Setup Requirements

The code uses the following packages that must be installed

• Keras
• Tensoflow
• SKLearn
• Numpy
• Matplotlib
• TQDM

Citation

If you find the following work useful please cite the paper-
@article{yedida2019novel, title={A novel adaptive learning rate scheduler for deep neural networks}, author={Yedida, Rahul and Saha, Snehanshu}, journal={arXiv preprint arXiv:1902.07399}, year={2019} }