Accelerating Constraint-Based Causal Discovery by Shifting Speed Bottleneck-Reference-Cited by-同舟云学术

Accelerating Constraint-Based Causal Discovery by Shifting Speed Bottleneck

Published:2022-02-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays
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Author:

Guo Ce¹,Luk Wayne¹

Affiliation:

1. Imperial College London, London, United Kingdom

Funder

Engineering and Physical Sciences Research Council

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3490422.3502363

Reference41 articles.

1. An empirical comparison of permutation methods for tests of partial regression coefficients in a linear model

2. PARTIAL CORRELATION AND CONDITIONAL CORRELATION AS MEASURES OF CONDITIONAL INDEPENDENCE

3. Léon Bottou . 2012. Stochastic gradient descent tricks . In Neural networks: Tricks of the trade . Springer , New York, NY, USA , 421--436. Léon Bottou. 2012. Stochastic gradient descent tricks. In Neural networks: Tricks of the trade . Springer, New York, NY, USA, 421--436.

4. Dynamic load balancing on single- and multi-GPU systems

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