Learning-Augmented Streaming Codes are Approximately Optimal for Variable-Size Messages-Reference-Cited by-同舟云学术

Learning-Augmented Streaming Codes are Approximately Optimal for Variable-Size Messages

Published:2022-06-26 Issue: Volume: Page:
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Container-title:2022 IEEE International Symposium on Information Theory (ISIT)
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Author:

Rudow Michael,Rashmi K.V.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9834325/9834269/09834539.pdf?arnumber=9834539

Reference50 articles.

1. Ko codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning;makkuva;International Conference on Machine Learning,2021

2. Hyper-graph-network decoders for block codes;nachmani;Advances in neural information processing systems,2019

3. Neural offset min-sum decoding

4. Deep Learning Methods for Improved Decoding of Linear Codes

5. On deep learning-based channel decoding

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