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Reverse Derivative Ascent: A Categorical Approach to Learning Boolean Circuits

  • Published:2021-02-08 Issue: Volume:333 Page:247-260
  • ISSN:2075-2180
  • Container-title:Electronic Proceedings in Theoretical Computer Science
  • language:en
  • Short-container-title:Electron. Proc. Theor. Comput. Sci.

Author:

Wilson Paul1,Zanasi Fabio2

Affiliation:

1. University of Southampton

2. University College London

Publisher

Open Publishing Association

Reference21 articles.

1. Information science and statistics;Bishop,2006

2. Rewriting modulo symmetric monoidal structure;Bonchi;Proceedings of the 31st Annual ACM/IEEE Symposium on Logic in Computer Science - LICS '16,2016

3. Reverse derivative categories;Cockett;arXiv:1910.07065 [cs, math],2019

4. BinaryConnect: Training Deep Neural Networks with binary weights during propagations;Courbariaux;arXiv:1511.00363 [cs]

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1. A Path to Safer Digital Systems Using Proactive Hazard Analysis in Logic Circuit Design;2024 35th Conference of Open Innovations Association (FRUCT);2024-04-24

2. Categorical Foundation of Explainable AI: A Unifying Theory;Communications in Computer and Information Science;2024

3. Dynamic Weight Distribution Method of Loss Function Based on Category Theory;Lecture Notes in Computer Science;2024

4. An axiomatic approach to differentiation of polynomial circuits;Journal of Logical and Algebraic Methods in Programming;2023-10

5. Jacobians and Gradients for Cartesian Differential Categories;Electronic Proceedings in Theoretical Computer Science;2022-11-03
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