Instance-based Learning
Instance-Based Learning is a supervised learning paradigm in which the model classifies new instances by comparing them to stored training instances, relying on similarity measures rather than explicitly generalizing a function.
842
Publications
53.8K
Citations
2.7K
Authors
966
Institutions
Publications per year
2017–2026
370
842
Improved Heterogeneous Distance Functions
D.R. Wilson, Tony Martinez · Journal of Artificial Intelligence Research · 1997 · 1.3K citations · Full text
From captions to visual concepts and back
Hao Fang, Saurabh Gupta, Forrest Iandola et al. · 2015 · 1.3K citations
Reduction Techniques for Instance-Based Learning Algorithms
D.R. Wilson, Tony Martinez · Machine Learning · 2000 · 1.2K citations · Full text
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Carnegie Mellon University
Pittsburgh, United States
24 h-index
82 publications
5.7K citations

Chinese Academy of Sciences
Beijing, China
17 h-index
59 publications
2.7K citations
Nanjing University of Science and Technology
Nanjing, China
16 h-index
37 publications
2K citations
University of Technology Sydney
Sydney, Australia
16 h-index
31 publications
1.6K citations
University of Córdoba
Córdoba, Spain
14 h-index
36 publications
1.4K citations
University of Chinese Academy of Sciences
Beijing, China
13 h-index
44 publications
2.5K citations

Shanghai Jiao Tong University
Shanghai, China
12 h-index
51 publications
2.6K citations
Nanjing University
Nanjing, China
12 h-index
32 publications
2.1K citations
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25 publications · 2.5K citations
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Repository · 29 publications · 916 citations
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Conference · 15 publications · 848 citations
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15 publications · 1.1K citations
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9 publications · 295 citations
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