Resource-Efficient Invariant Networks: Exponential Gains by Unrolled Optimization

@article{Buchanan2022ResourceEfficientIN,
  title={Resource-Efficient Invariant Networks: Exponential Gains by Unrolled Optimization},
  author={Sam Buchanan and Jingkai Yan and Ellie Haber and John N. Wright},
  journal={ArXiv},
  year={2022},
  volume={abs/2203.05006}
}
2022 Abstract Achieving invariance to nuisance transformations is a fundamental challenge in the construction of robust and reliable vision systems. Existing approaches to invariance scale exponentially with the dimension of the family of transformations, making them unable to cope with natural variabilities in visual data such as changes in pose and perspective. We identify a common limitation of these approaches—they rely on sampling to traverse the high-dimensional space of transformations… 

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