Jyh-Han Lin

700 total citations
12 papers, 446 citations indexed

About

Jyh-Han Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Jyh-Han Lin has authored 12 papers receiving a total of 446 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Jyh-Han Lin's work include Machine Learning and Algorithms (7 papers), Machine Learning and Data Classification (5 papers) and Algorithms and Data Compression (4 papers). Jyh-Han Lin is often cited by papers focused on Machine Learning and Algorithms (7 papers), Machine Learning and Data Classification (5 papers) and Algorithms and Data Compression (4 papers). Jyh-Han Lin collaborates with scholars based in United States and China. Jyh-Han Lin's co-authors include Jeffrey Scott Vitter, Liqun Li, Chunshui Zhao, Thomas Moscibroda, Guobin Shen and Feng Zhao and has published in prestigious journals such as Machine Learning, Information and Computation and Information Processing Letters.

In The Last Decade

Jyh-Han Lin

11 papers receiving 416 citations

Peers

Jyh-Han Lin

CNC

AI

EEE

OBHRM

CTM

Donald K. Wagner United States

C.W. Duin Netherlands

Y. F. Wu United States

Sergei Bespamyatnikh Canada

Manabu Shirosaki Japan

Gintaras Palubeckis Lithuania

Jérôme Monnot France

Yuqi Chen China

Giulia Galbiati Italy

Frances Yao United States

Donald K. Wagner United States

Jyh-Han Lin

140 ×0.8

CNC

69 ×0.5

AI

93 ×0.9

EEE

18 ×0.2

OBHRM

170 ×1.7

CTM

Citations per year, relative to Jyh-Han Lin Jyh-Han Lin (= 1×) peers Donald K. Wagner

Countries citing papers authored by Jyh-Han Lin

Since Specialization

Citations

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

Fields of papers citing papers by Jyh-Han Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jyh-Han Lin. 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 Jyh-Han Lin. The network helps show where Jyh-Han Lin may publish in the future.

Co-authorship network of co-authors of Jyh-Han Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Jyh-Han Lin. A scholar is included among the top collaborators of Jyh-Han Lin 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 Jyh-Han Lin. Jyh-Han Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Li, Liqun, Guobin Shen, Chunshui Zhao, et al.. (2014). Experiencing and handling the diversity in data density and environmental locality in an indoor positioning service. 459–470. 93 indexed citations

2.

Lin, Jyh-Han & Jeffrey Scott Vitter. (2003). Nearly optimal vector quantization via linear programming. KU ScholarWorks (The University of Kansas). 22–31.

3.

Lin, Jyh-Han & Jeffrey Scott Vitter. (1994). A Theory for Memory-Based Learning. Machine Learning. 17(2-3). 143–167. 1 indexed citations

4.

Lin, Jyh-Han & Jeffrey Scott Vitter. (1994). A theory for memory-based learning. Machine Learning. 17(2-3). 143–167. 6 indexed citations

5.

Vitter, Jeffrey Scott & Jyh-Han Lin. (1992). Learning in parallel. Information and Computation. 96(2). 179–202. 12 indexed citations

6.

Lin, Jyh-Han & Jeffrey Scott Vitter. (1992). Approximation algorithms for geometric median problems. Information Processing Letters. 44(5). 245–249. 101 indexed citations

7.

Lin, Jyh-Han & Jeffrey Scott Vitter. (1992). A theory for memory-based learning. 103–115. 13 indexed citations

8.

Lin, Jyh-Han & Jeffrey Scott Vitter. (1992). e-approximations with minimum packing constraint violation (extended abstract). 771–782. 122 indexed citations

9.

Lin, Jyh-Han & Jeffrey Scott Vitter. (1991). Complexity results on learning by neural nets. Machine Learning. 6(3). 211–230. 33 indexed citations

10.

Lin, Jyh-Han & Jeffrey Scott Vitter. (1991). Complexity Results on Learning by Neural Nets. Machine Learning. 6(3). 211–230. 61 indexed citations

11.

Lin, Jyh-Han & Jeffrey Scott Vitter. (1989). Complexity issues in learning by neural nets. Conference on Learning Theory. 118–133. 1 indexed citations

12.

Vitter, Jeffrey Scott & Jyh-Han Lin. (1988). Learning in parallel. Conference on Learning Theory. 106–124. 3 indexed citations

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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