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Quantitative convergence analysis of kernel based large-margin unified machines
Jun FAN
, Dao Hong Xiang
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Corresponding author for this work
Department of Mathematics
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Mathematics
Approximation
12%
Binary Classification
68%
Classification Algorithm
35%
Classifier
56%
Community
25%
Convergence Analysis
69%
Family
11%
Framework
14%
High-dimensional
20%
Higher Dimensions
46%
kernel
51%
Loss Function
25%
Machine Learning
27%
Margin
85%
Performance
14%
Projection Operator
28%
Quantitative Analysis
92%
Reproducing Kernel Hilbert Space
56%
Sample Size
38%
Support Vector
38%
Support Vector Machine
62%
Training Samples
33%
Engineering & Materials Science
Classifiers
53%
Hilbert spaces
100%
Machine learning
27%
Piles
35%
Support vector machines
60%