On Arbitrary Ignorance of Stragglers with Gradient Coding
Author:
Affiliation:
1. Graduate Center, City University of New York
2. Arch
3. Queens College and Graduate Center, City University of New York
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10272385/10272393/10272463.pdf?arnumber=10272463
Reference33 articles.
1. Straggler Mitigation in Distributed Matrix Multiplication: Fundamental Limits and Optimal Coding
2. Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication;yu;Proceedings of the 31st International Conference on Neural Information Processing Systems (NIPS),0
3. Dual Entangled Polynomial Code: Three-Dimensional Coding for Distributed Matrix Multiplication;soto;Proceedings of the 36th International Conference on Machine Learning,0
4. “Short-Dot”: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products
5. A REVISION OF MINTY'S ALGORITHM FOR FINDING A MAXIMUM WEIGHT STABLE SET OF A CLAW-FREE GRAPH
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