Skip to content

Experiments for the JMLR paper "Optimal Convergence Rates for Distributed Nystroem Approximation"

Notifications You must be signed in to change notification settings

superlj666/DNystroem

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1 Commit
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Distributed Nystroem Approximation

Intro

This repository provides the code used to run the experiments of the JMLR paper "Optimal Convergence Rates for Distributed Nystroem Approximation".

Environments

  • Python 3.9.15
  • Pytorch 1.13.0
  • NNI 2.10
  • CUDA 11.7
  • cuDnn 8.2.1
  • GPU: Nvidia RTX 2080Ti 11GB

Core functions

  • functions/algorithms.py implements all compared methods.
  • functions/experiments.py construct repeatable experiments in the paper.
  • functions/optimal_parameters.py records optimal parameters for the proposed algorithm.
  • functions/utils.py defines data loaders and evaluation measures.
  • tune_hyperparameter.py uses NNI framework to tune the optimal hyperparameters.

Experiments

  1. Download datasets from UCI datasets.
  2. Run the script to tune parameters via NNI and record them in optimal_parameters.py.
python tune_hyperparameter.py
  1. Run the script to obtain results in Experiment section, which will be saved in results folder.
python runscripts.py
  1. Use plot.ipynb to draw figures from the experiment results.

About

Experiments for the JMLR paper "Optimal Convergence Rates for Distributed Nystroem Approximation"

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published