This repository contains codes on the implementation of Divide2Conquer (D2C), a novel technique designed to address Overfitting. The separate folders contain samples of different types of experiments on different datasets from different domains. Our experiments were performed using Google Colab. Both A100 and V100 GPUs were used. Some packages may have updated versions now (e.g. Keras).

If you find this work useful in your research, please consider citing our paper:

@INPROCEEDINGS{siddiqui2024d2c,
  author={Bari Siddiqui, Md. Saiful and Mohaiminul Islam, Md and Rabiul Alam, Md. Golam},
  booktitle={2024 IEEE International Conference on Big Data (BigData)},
  title={Divide2Conquer (D2C): A Decentralized Approach Towards Overfitting Remediation in Deep Learning},
  year={2024},
  volume={},
  number={},
  pages={1458-1463},
  doi={10.1109/BigData62323.2024.10826082}}

This project is licensed under the MIT License. See the LICENSE file for details.