LightLT: A Lightweight Representation Quantization Framework for Long-Tail Data-Reference-Cited by-同舟云学术

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LightLT: A Lightweight Representation Quantization Framework for Long-Tail Data

Published:2024-05-13 Issue: Volume:27 Page:1380-1393
ISSN:
Container-title:2024 IEEE 40th International Conference on Data Engineering (ICDE)
language:
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Author:

Wang Haoyu¹,Li Ruirui²,Wang Zhengyang²,Tang Xianfeng²,Zhang Danqing²,Cheng Monica²,Yin Bing²,Droppo Jasha³,Wang Suhang⁴,Gao Jing¹

Affiliation:

1. School of Electrical and Computer Engineering, Purdue University,West Lafayette,United States

2. Amazon,Palo Alto,United States

3. Amazon,Sunnyvale,United States

4. College of Information Sciences and Technology, Pennsylvania State University,University Park,United States

Funder

US National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10597630/10597390/10598002.pdf?arnumber=10598002

Reference83 articles.

1. Deep Residual Learning for Image Recognition

2. Bert: Pre-training of deep bidirectional transformers for language understanding;Devlin;arXiv preprint,2018

3. Image retrieval

4. Content-based image retrieval: A review of recent trends

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