Han Cai

73 papers receiving 2.6k citations

Han Cai's Hit Papers

Efficient Architecture Search by Network Transformation 2018 · 300 citations
3000+3+6Years since publication100200300400

Peers

Han Cai
Comparison fields: 5 of 132
  • Computer Vision and Pattern Recognition 848
  • Artificial Intelligence 1.0k
  • Computer Networks and Communications 494
  • Information Systems 444
  • Transportation 75
Replace Kyong-Ho Lee with:
Kyong-Ho Lee South Korea
Wei Zhang China
Takeshi Yamada Japan
Jing Zhang China
Han Hu China
Yantao Li China
Wenjun Jiang China
Shi Cheng China
Jian Yuan China
Han Cai relative to Kyong-Ho Lee South Korea Kyong-Ho Lee's profile →
Citations per field
00.5×
Kyong-Ho Lee · 1×
Citations per year

Countries citing papers authored by Han Cai

Since Specialization
Citations

This map shows the geographic impact of Han Cai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Han Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Han Cai more than expected).

Fields of papers citing papers by Han Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Han Cai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Han Cai. The network helps show where Han Cai may publish in the future.

Co-authors

The 25 scholars most cited alongside Han Cai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Han Cai Line = papers co-authored together Han Cai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Product-Based Neural Networks for User Response Prediction
Hit paper breakdown →
2016400
2
Efficient Architecture Search by Network Transformation
Hit paper breakdown →
2018300
3 2018224
4 2020139
5 2020122
6 2021115
7 2007102
8 200999
9 201993
10 202289
11 201888
12 200685
13 202274
14 202067
15 200958
16 200853
17 200551
18 202138
19
TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning
202029
20 202429

About Han Cai

Han Cai is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Artificial Intelligence, Condensed Matter Physics and Computer Vision and Pattern Recognition, having authored 79 papers that have together received 2.6k indexed citations. Recurring topics across this work include Physics of Superconductivity and Magnetism (14 papers), Quantum and electron transport phenomena (9 papers), Mobile Ad Hoc Networks (9 papers), Advanced Neural Network Applications (8 papers), Opportunistic and Delay-Tolerant Networks (7 papers), Advanced Wireless Network Optimization (6 papers), Conducting polymers and applications (5 papers) and Advanced Sensor and Energy Harvesting Materials (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (848 citations), Artificial Intelligence (1.0k citations), Computer Networks and Communications (494 citations), Information Systems (444 citations) and Transportation (75 citations). Han Cai has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Weinan Zhang, Yong Yu, Do Young Eun, Song Han, Jun Wang, Tianyao Chen, Kan Ren, Ying Wen, Jun Wang and Yanru Qu. Their work appears in journals such as IEEE Transactions on Applied Superconductivity, Applied Physics Letters, IEEE Transactions on Electron Devices, Advanced Energy Materials and IEEE/ACM Transactions on Networking.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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