Don Hush

1.7k citations
44 papers · 963 · h-index 17

Impact in

Papers in

    • Neural Networks and Applications 13
    • Machine Learning and Algorithms 6
    • Machine Learning and Data Classification 4
    • Anomaly Detection Techniques and Applications 4
    • Fuzzy Logic and Control Systems 4
    • Machine Learning and ELM 3
    • Face and Expression Recognition 7
    • Advanced Image and Video Retrieval Techniques 4

Don Hush

42 papers receiving 901 citations

Peers

Don Hush
Comparison fields: 5 of 113
  • Artificial Intelligence 573
  • Statistics and Probability 133
  • Computer Vision and Pattern Recognition 237
  • Signal Processing 78
  • Computational Mathematics 4
Replace Gilles Blanchard with:
Gilles Blanchard Germany
Ding Zhou China
Cédric Archambeau United Kingdom
Alexander Rakhlin United States
Tim van Erven Netherlands
Jinwoo Shin South Korea
Krikamol Muandet Germany
Mahdi Soltanolkotabi United States
Purushottam Kar India
Don Hush relative to Gilles Blanchard Germany Gilles Blanchard's profile →
Citations per field
00.5×1.5×
Gilles Blanchard · 1×
Citations per year

Countries citing papers authored by Don Hush

Since Specialization
Citations

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

Fields of papers citing papers by Don Hush

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Don Hush. 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 Don Hush. The network helps show where Don Hush may publish in the future.

Co-authors

The 23 scholars most cited alongside Don Hush, 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 Don Hush Line = papers co-authored together Don Hush links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Classification Framework for Anomaly Detection
2005171
2 1996122
3
Optimal Rates for Regularized Least Squares Regression.
2009106
4 200874
5 200352
6 201049
7 199649
8
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
200644
9
Training SVMs without offset
200935
10 201122
11 201322
12
Predicting Student Enrollment Based on Student and College Characteristics.
201821
13 201019
14 201619
15 201019
16 200517
17 199917
18
Density Level Detection is Classification
200414
19 199414
20 201910

About Don Hush

Don Hush is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Mathematical Physics and Control and Systems Engineering, having authored 44 papers that have together received 963 indexed citations. Recurring topics across this work include Neural Networks and Applications (13 papers), Face and Expression Recognition (7 papers), Machine Learning and Algorithms (6 papers), Machine Learning and Data Classification (4 papers), Anomaly Detection Techniques and Applications (4 papers), Fuzzy Logic and Control Systems (4 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Machine Learning and ELM (3 papers). The work is most often cited by research in Artificial Intelligence (573 citations), Statistics and Probability (133 citations), Computer Vision and Pattern Recognition (237 citations), Signal Processing (78 citations) and Computational Mathematics (4 citations). Don Hush has collaborated with scholars based in United States, France and Colombia. Frequent co-authors include Clint Scovel, Ingo Steinwart, Mary M. Moya, Bill G. Horne, Reid Porter, James Theiler, Andrew M. Fraser, Patrick J. Kelly, S.D. Stearns and Ahmad Slim. Their work appears in journals such as Machine Learning, Neural Networks, Journal of Machine Learning Research, IEEE Signal Processing Magazine and Journal of Multivariate Analysis.

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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