/stability_ho

Primary LanguagePythonMIT LicenseMIT

Stability and Generalization of Bilevel Programming in Hyperparameter Optimization

Codes for Stability and Generalization of Bilevel Programming in Hyperparameter Optimization.

Requirements

The codes are implemented on

  • Python=3.7
  • PyTorch=1.4.0

Run codes

python fl_omniglot.py  # run feature learning experiments

python rw_mnist.py  # run data reweighting experiments

The experiment to run is controlled by the tag variable in the above *.py files. For instance,

  • tag = ablo_K will run the UD algorithm with different K
  • tag = rs_K will run the random search algorithm with different K
  • tag = wdh will run the UD algorithm with different weight decay in the outer level
  • tag = wdl will run the UD algorithm with different weight decay in the inner level

You can also specify other settings by modify the args variable in the above *.py files.