Accelerating Deep Learning Classification with Error-controlled Approximate-key Caching-Reference-Cited by-同舟云学术

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Accelerating Deep Learning Classification with Error-controlled Approximate-key Caching

Published:2022-05-02 Issue: Volume: Page:
ISSN:
Container-title:IEEE INFOCOM 2022 - IEEE Conference on Computer Communications
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Author:

Finamore Alessandro¹,Roberts James¹,Gallo Massimo¹,Rossi Dario¹

Affiliation:

1. HUAWEI Technologies,France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9796607/9796652/09796677.pdf?arnumber=9796677

Reference52 articles.

1. Locality-Sensitive Hashing for Finding Nearest Neighbors [Lecture Notes]

2. Deep Learning and Zero-Day Traffic Classification: Lessons Learned From a Commercial-Grade Dataset

3. Do Switches Dream of Machine Learning?

4. A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

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1. Adapting Neural Networks at Runtime: Current Trends in At-Runtime Optimizations for Deep Learning;ACM Computing Surveys;2024-05-14

2. TTL model for an LRU-based similarity caching policy;Computer Networks;2024-03

3. ISAC: In-Switch Approximate Cache for IoT Object Detection and Recognition;IEEE INFOCOM 2023 - IEEE Conference on Computer Communications;2023-05-17

4. GRADES: Gradient Descent for Similarity Caching;IEEE/ACM Transactions on Networking;2023-02

5. Computing the Hit Rate of Similarity Caching;GLOBECOM 2022 - 2022 IEEE Global Communications Conference;2022-12-04

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