Active Learning With Gaussian Processes
Active Learning with Gaussian Processes is a machine learning framework that iteratively selects the most informative data points for labeling by leveraging the probabilistic predictions and uncertainty estimates of a Gaussian process model to optimize the training data acquisition process.
97
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5.2K
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269
Authors
131
Institutions
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2017–2026
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Active Learning with Gaussian Processes for Object Categorization
Ashish Kapoor, Kristen Grauman, Raquel Urtasun et al. · 2007 · 330 citations
Gaussian Processes for Object Categorization
Ashish Kapoor, Kristen Grauman, Raquel Urtasun et al. · International Journal of Computer Vision · 2009 · 185 citations · Full text
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ETH Zurich
Zurich, Switzerland
5 h-index
11 publications
1.4K citations
The University of Texas at Austin
Austin, United States
5 h-index
8 publications
645 citations
Microsoft (United States)
Redmond, United States
5 h-index
9 publications
1.1K citations
University of Sheffield
Sheffield, United Kingdom
4 h-index
12 publications
906 citations
University of Cambridge
Cambridge, United Kingdom
4 h-index
6 publications
353 citations

East China Normal University
Shanghai, China
3 h-index
8 publications
138 citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
4 publications
487 citations

Stevens Institute of Technology
Hoboken, United States
3 h-index
5 publications
297 citations
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Repository · 8 publications · 153 citations
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5 publications · 164 citations
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2 publications · 241 citations
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