python implementation of online learning to learn non-smooth algorithms.
This repository requires
Exps from "Learning-to-Learn Stochastic Gradient Descent with Biased Regularization"
This repo contains the code for the experiments of the paper "Learning-to-Learn Stochastic Gradient Descent with Biased Regularization" (https://arxiv.org/abs/1903.10399v1)
For the synthetic experiments run
exp_synthetic.py while for the computer survey experiments run
You can find the implementation of the algorithms discussed in the paper inside
algorithms.py, while the dataset generation
and loading functions are in
Experiments results will be stored in a folder inside
exps with a descriptive name containing details about the
experiments' parameters (more details in
If you have any problems feel free to contact me or open an issue.