基本信息
浏览量:18
职业迁徙
个人简介
My primary research focus lies in efficient deep learning, where my investigations center around techniques to achieve a lightweight and resource-efficient deep learning model, without compromising on its accuracy or performance. The objective of my research is to design and develop innovative methods to compress deep learning models, such as pruning, quantization, low-rank approximation. By reducing the size and complexity of these models, I aim to enable their deployment on devices with limited computational resources, such as mobile phones and embedded systems, thus expanding the accessibility and applicability of deep learning in real-world applications.
研究兴趣
论文共 29 篇作者统计合作学者相似作者
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期刊级别
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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION (2024)
2024 DATA COMPRESSION CONFERENCE, DCCpp.582-582, (2024)
ECCV 2024 (2024)
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2024 DATA COMPRESSION CONFERENCE, DCCpp.583-583, (2024)
arXiv (Cornell University) (2024)
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2024)
PROCEEDINGS OF THE 2023 THE 50TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE, ISCA 2023pp.950-962, (2023)
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作者统计
#Papers: 29
#Citation: 230
H-Index: 5
G-Index: 11
Sociability: 4
Diversity: 2
Activity: 34
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