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Code for Sample Efficient Learning of Predictors that Complement Humans (ICML 2022)

Python 50.04% Jupyter Notebook 49.96%

active_learn_to_defer's Introduction

Sample Efficient Learning of Predictors that Complement Humans

We provide two jupyter notebooks each replicates one of the figures in our paper:

joint_v_staged_model_complex.ipynb replicates Figure 2
joint_v_staged_sample_complexity.ipynb replicates Figure 3
python run_halfspaces.py replicates Figure 4

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