Charles X. Ling

9.4k citations
131 papers · 5.7k indexed · 1 hit paper · h-index 29
Topics
Machine Learning and Data Classification (34 papers)Imbalanced Data Classification Techniques (29 papers)Machine Learning and Algorithms (22 papers)
Partner nations
CanadaChinaUnited States

In The Last Decade

Charles X. Ling

123 papers receiving 5.3k citations

Hit Papers

Using AUC and accuracy in evaluating learning algorithms2005202620122019200550010001.5k

Peers

Charles X. Ling
Comparison fields: 5 of 202
  • Artificial Intelligence 3.3k
  • Information Systems 1.2k
  • Computer Vision and Pattern Recognition 700
  • Computational Theory and Mathematics 665
  • Molecular Biology 552
Replace Oded Maimon with:
Oded Maimon Israel
Marc K. Albert United States
Stan Matwin Canada
Mark A. Hall New Zealand
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Petra Perner Germany
Robert C. Holte Canada
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Miroslav Kubát United States
Charles X. Ling relative to Oded Maimon Israel Oded Maimon's profile →
Citations per field
00.5×
Oded Maimon · 1×
Citations per year

Countries citing papers authored by Charles X. Ling

Since Specialization
Citations

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

Fields of papers citing papers by Charles X. Ling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charles X. Ling. 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 Charles X. Ling. The network helps show where Charles X. Ling may publish in the future.

Co-authorship network of co-authors of Charles X. Ling

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 4
4 1
5 1
6 4
7 8
8 9
9
Triply Stochastic Gradients on Multiple Kernel Learning.
8
10
A New Generalized Error Path Algorithm for Model Selection
12
11
Data sparseness in linear SVM
8
12 6
13
Cost-sensitive test strategies
23
14 19
15
Decision tree with better ranking
36
16
Learnability of Augmented Naive Bayes in Nonimal Domains
4
17
Data mining for direct marketing: problems and solutions
443
18
Alignment algorithms for learning to read aloud
2
19
A Symbolic Model for Learning the Past-Tenses of English Verbs.
3
20
Constructive Inductive Logic Programming.
12

About Charles X. Ling

Charles X. Ling is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 131 papers that have together received 5.7k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (34 papers), Imbalanced Data Classification Techniques (29 papers) and Machine Learning and Algorithms (22 papers). The work is most often cited by research in Artificial Intelligence (3.3k citations), Information Systems (1.2k citations) and Health Information Management (215 citations). Charles X. Ling has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Jin Huang, LI Cheng-hui, Wenyin Gong, Zhihua Cai, Victor S. Sheng, Jin Huang, Qiang Yang, Harry Zhang, Shichao Zhang and Hui Li. Their work appears in journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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Rankless by CCL
2026