Li-Yang Tan

721 citations
37 papers · 174 · h-index 7

Impact in

Papers in

    • Complexity and Algorithms in Graphs 27
    • Advanced Graph Theory Research 6
    • semigroups and automata theory 4
    • Machine Learning and Algorithms 19
    • Algorithms and Data Compression 8
    • Machine Learning and Data Classification 5
    • Cryptography and Data Security 4

Li-Yang Tan

29 papers receiving 157 citations

Peers

Li-Yang Tan
Comparison fields: 5 of 30
  • Computational Theory and Mathematics 119
  • Discrete Mathematics and Combinatorics 12
  • Artificial Intelligence 102
  • Computer Graphics and Computer-Aided Design 11
  • Statistics and Probability 23
Replace Kevin Matulef with:
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Citations per field
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Citations per year

Countries citing papers authored by Li-Yang Tan

Since Specialization
Citations

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

Fields of papers citing papers by Li-Yang Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Li-Yang Tan. 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 Li-Yang Tan. The network helps show where Li-Yang Tan may publish in the future.

Co-authors

The 25 scholars most cited alongside Li-Yang Tan, 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 Li-Yang Tan Line = papers co-authored together Li-Yang Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201025
2 201621
3 201519
4 201315
5 201413
6 20169
7 20188
8 20145
9 20145
10 20165
11 20175
12 20195
13 20175
14
20144
15 20224
16 20223
17
Attribute-Efficient Learning and Weight-Degree Tradeoffs for Polynomial Threshold Functions
20123
18 20173
19 20203
20
20132

About Li-Yang Tan

Li-Yang Tan is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Discrete Mathematics and Combinatorics, Electrical and Electronic Engineering and Computer Graphics and Computer-Aided Design, having authored 37 papers that have together received 174 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (27 papers), Machine Learning and Algorithms (19 papers), Algorithms and Data Compression (8 papers), Advanced Graph Theory Research (6 papers), Machine Learning and Data Classification (5 papers), Cryptography and Data Security (4 papers), semigroups and automata theory (4 papers) and Computational Geometry and Mesh Generation (3 papers). The work is most often cited by research in Computational Theory and Mathematics (119 citations), Discrete Mathematics and Combinatorics (12 citations), Artificial Intelligence (102 citations), Computer Graphics and Computer-Aided Design (11 citations) and Statistics and Probability (23 citations). Li-Yang Tan has collaborated with scholars based in United States, Canada and Japan. Frequent co-authors include Rocco A. Servedio, Ryan O’Donnell, Ilias Diakonikolas, Prasad Raghavendra, Xi Chen, Anindya De, Omer Tamuz, Raghu Meka, Adam R. Klivans and Benjamin Rossman. Their work appears in journals such as Journal of the ACM, SIAM Journal on Computing, Theory of Computing, Stochastic Processes and their Applications and SHILAP Revista de lepidopterología.

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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