Hashing Encoding
Hashing Encoding is a categorical encoding technique that maps high-cardinality categorical variables into a lower-dimensional space of fixed size through a hash function, thereby reducing memory usage and mitigating issues associated with traditional encoding methods in the presence of sparse or evolving categorical data.
80
Publications
5.5K
Citations
276
Authors
126
Institutions
Publications per year
2017–2026
42
Parents
80
HashNet: Deep Learning to Hash by Continuation
Zhangjie Cao, Mingsheng Long, Jianmin Wang et al. · 2017 · 713 citations
Locality-sensitive binary codes from shift-invariant kernels
Maxim Raginsky, Svetlana Lazebnik · 2009 · 620 citations
Jae‐Pil Heo, Youngwoon Lee, Junfeng He et al. · 2012 · 382 citations
1–5 of 80
276
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Korea Advanced Institute of Science and Technology, South Korea
2 publications · 495 citations
2
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2
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National Institute Of Technology Silchar, India
2 publications · 47 citations
2
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1–5 of 276
126

University of Electronic Science and Technology of China
Chengdu, China
4 h-index
9 publications
313 citations

Zhejiang University
Hangzhou, China
3 h-index
13 publications
551 citations
Columbia University
New York, United States
3 h-index
4 publications
899 citations
Tsinghua University
Beijing, China
3 h-index
7 publications
2.9K citations
National Institute Of Technology Silchar
Silchar, India
3 h-index
9 publications
196 citations
Meta (Israel)
Tel Aviv, Israel
2 h-index
5 publications
169 citations
Microsoft Research Asia (China)
Beijing, China
2 h-index
5 publications
1.5K citations

Xi'an Jiaotong University
Xi'an, China
2 h-index
9 publications
297 citations
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6 publications · 231 citations
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4 publications · 123 citations
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4 publications · 110 citations
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3 publications · 138 citations
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2 publications · 37 citations
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