Boosted Race Trees for Low Energy Classification-Reference-Cited by-同舟云学术

Boosted Race Trees for Low Energy Classification

Published:2019-04-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems
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Author:

Tzimpragos Georgios¹,Madhavan Advait²,Vasudevan Dilip³,Strukov Dmitri⁴,Sherwood Timothy¹

Affiliation:

1. University of California, Santa Barbara, Santa Barbara, CA, USA

2. National Institute of Standards and Technology & University of Maryland, Gaithersburg & College Park, MD, USA

3. Lawrence Berkeley National Labs, Berkeley, CA, USA

4. University of California Santa Barbara, Santa Barbara, CA, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3297858.3304036

Reference42 articles.

1. M. Bavandpour M. R. Mahmoodi and D. B. Strukov. 2019. Energy-Efficient Time-Domain Vector-by-Matrix Multiplier for Neurocomputing and Beyond. IEEE Transactions on Circuits and Systems II: Express Briefs (2019) 1--1. M. Bavandpour M. R. Mahmoodi and D. B. Strukov. 2019. Energy-Efficient Time-Domain Vector-by-Matrix Multiplier for Neurocomputing and Beyond. IEEE Transactions on Circuits and Systems II: Express Briefs (2019) 1--1.

2. A compact 3-D VLSI classifier using bagging threshold network ensembles

3. Future of interconnect fabric

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