Dělen: Enabling Flexible and Adaptive Model-serving for Multi-tenant Edge AI

Author:

Liang Qianlin1ORCID,Hanafy Walid A.1ORCID,Bashir Noman1ORCID,Ali-Eldin Ahmed2ORCID,Irwin David1ORCID,Shenoy Prashant1ORCID

Affiliation:

1. Manning College of Information & Computer Sciences, University of Massachusetts Amherst, United States of America

2. Manning College of Information & Computer Sciences, University of Massachusetts Amherst, USA and Department of Computer Science and Engineering, Chalmers University of Technology, Sweden

Funder

Adobe Systems

National Science Foundation

US Army Contract

Amazon Web Services

Publisher

ACM

Reference56 articles.

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3. Always-on Vision Processing Unit for Mobile Applications

4. Tolga Bolukbasi , Joseph Wang , Ofer Dekel , and Venkatesh Saligrama . 2017 . Adaptive Neural Networks for Efficient Inference . In Proceedings of the 34th International Conference on Machine Learning - Volume 70 (Sydney, NSW, Australia) (ICML’17). JMLR.org, 527–536. Tolga Bolukbasi, Joseph Wang, Ofer Dekel, and Venkatesh Saligrama. 2017. Adaptive Neural Networks for Efficient Inference. In Proceedings of the 34th International Conference on Machine Learning - Volume 70 (Sydney, NSW, Australia) (ICML’17). JMLR.org, 527–536.

5. Food-101 – Mining Discriminative Components with Random Forests

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