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defuse's Introduction

Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction

Environment Requirement

The code has been tested running under Python 3.8.10. The required packages are follows:

  • numpy==1.18.5
  • tqdm==4.61.2
  • pandas==1.3.1
  • scikit_learn==1.0.2
  • tensorflow==2.4.1

Example to Run the Codes

The instruction of commands has been clearly stated in the shell scripts: We uploaded some shell scripts as a reference to run the code, however, the pathes should be modified accordingly.

  • run_pretrain.sh:
pretrain ckpts using the first 30 days information. we also provide the model checkpoints to reproduce the results on the public Criteo30d.
  • run_base(_1d).sh
obtain baseline results under streaming setting.
  • run_defuse.sh
obtain our DEFUSE results.

Dataset

The criteo dataset is available at https://drive.google.com/file/d/1x4KktfZtls9QjNdFYKCjTpfjM4tG2PcK/view?usp=sharing

A preprint version of this paper is available at https://arxiv.org/abs/2202.06472.pdf

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