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Active Learning with Logged Data

This repository contains a python implementation of experiments in paper:

Songbai Yan, Kamalika Chaudhuri, Tara Javidi. "Active Learning with Logged Data." Proceedings of the 35th International Conference on Machine Learning, PMLR 80:5521-5530, 2018.

File Descriptions

  • algos.py Implementation of active learning algorithms
  • data.py Preprocessing of data sets
  • experiments.py Implementation of experiments
  • logger.py Logging information for plots and reports
  • main.py The main file
  • model.py Implementation of a linear model
  • opt.py Implementation of stochastic gradient descent with weighted samples
  • utils.py Auxiliary functions

Data sets should be put in "../data", and results are located in "../results/".

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