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README.md added Readme file Oct 25, 2019

README.md

Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum

This repository accompanies the research paper, Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum (accepted at NeurIPS 2019).

Citation

@article{saxena2019data,
  title={Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum},
  author={Saxena, Shreyas and Tuzel, Oncel and DeCoste, Dennis},
  booktitle={Advances in neural information processing systems},
  year={2019}
}

Data Parameters

In the paper cited above, we have introduced a new family of parameters termed "data parameters". Specifically, we equip each class and training data point with a learnable parameter (data parameters), which governs their importance during different stages of training. Along with the model parameters, the data parameters are also learnt with gradient descent, thereby yielding a curriculum which evolves during the course of training. More importantly, post training, during inference, data parameters are not used, and hence do not alter the model's complexity or run-time at inference.

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