Yu-Chin Juan

1.3k citations
7 papers · 676 indexed · 1 hit paper · h-index 6
Topics
Recommender Systems and Techniques (6 papers)Stochastic Gradient Optimization Techniques (4 papers)Advanced Bandit Algorithms Research (2 papers)
Partner nations
TaiwanUnited States

In The Last Decade

Yu-Chin Juan

7 papers receiving 657 citations

Hit Papers

Field-aware Factorization Machines for CTR Prediction20162026201920222016100200300400

Peers

Yu-Chin Juan
Comparison fields: 5 of 70
  • Information Systems 469
  • Artificial Intelligence 337
  • Computer Vision and Pattern Recognition 296
  • Computer Networks and Communications 84
  • Management Science and Operations Research 84
Replace Wei-Sheng Chin with:
Wei-Sheng Chin Taiwan
Lan Nie United States
Weijie Bian China
Weihong Wang China
Yilei Zhang Hong Kong
T. Ryan Hoens United States
Wensi Xi United States
Zhankui He United States
Mohammad Yahya H. Al-Shamri Saudi Arabia
Bottyán Németh Hungary
Yu-Chin Juan relative to Wei-Sheng Chin Taiwan Wei-Sheng Chin's profile →
Citations per field
00.5×1.5×
Wei-Sheng Chin · 1×
Citations per year

Countries citing papers authored by Yu-Chin Juan

Since Specialization
Citations

This map shows the geographic impact of Yu-Chin Juan'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 Yu-Chin Juan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu-Chin Juan more than expected).

Fields of papers citing papers by Yu-Chin Juan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu-Chin Juan. 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 Yu-Chin Juan. The network helps show where Yu-Chin Juan may publish in the future.

Co-authorship network of co-authors of Yu-Chin Juan

This figure shows the co-authorship network connecting the top 25 collaborators of Yu-Chin Juan. A scholar is included among the top collaborators of Yu-Chin Juan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yu-Chin Juan. Yu-Chin Juan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 1
2 8
3 54
4
LIBMF: a library for parallel matrix factorization in shared-memory systems
21
5
Field-aware Factorization Machines for CTR Predictionbreakdown →
430
6 71
7 91

About Yu-Chin Juan

Yu-Chin Juan is a scholar working on Information Systems, Numerical Analysis and Management Science and Operations Research, having authored 7 papers that have together received 676 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (6 papers), Stochastic Gradient Optimization Techniques (4 papers) and Advanced Bandit Algorithms Research (2 papers). The work is most often cited by research in Computational Mathematics (15 citations), Information Systems (469 citations) and Computer Vision and Pattern Recognition (296 citations). Yu-Chin Juan has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Chih‐Jen Lin, Yong Zhuang, Wei-Sheng Chin, Olivier Chapelle, Mengyuan Yang, Guo-Xun Yuan and Jiacong Shen. Their work appears in journals such as Journal of Machine Learning Research and ACM Transactions on Intelligent Systems and Technology.

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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