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(1)
Statistical Learning Theory
Related Publications
(8)
Text categorization with support vector machines: Learning withmany relevant features
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The nature of statistical learning theory
The nature of statistical learning theory,V. Vapnic
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The nature of statistical learning theory
(
Citations: 9780
)
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V. Vapnic
Published in 1995.
Cumulative
Annual
Citation Context
(5928)
...Support vector machine (SVM) [3], [
44
] is a widely used machine learning technique and has been applied successfully to many realworld applications [8]...
...complexity [
44
]; C is the parameter to trade off the model complexityandthesumoflossesofthetrainingbags; � iy isthe amplification coefficient of the loss � i for handing the class imbalance problem...
...The procedure of solving the optimization problem (1) is called “training,” and it has been proved that the training procedure depends only on the data through dot products in H [3], [
44
], i.e., on functions of the form KðXi ;X j Þ¼ h� ðXiÞ ;� ðXjÞi where KðXi ;X jÞ is called “kernel function;” Xi and Xj denote two arbitrary training bags...
...In fact, kernel function is very crucial in support vector machine and needs to be predefined [
44
]...
YingXin Li
,
et al.
Drosophila Gene Expression Pattern Annotation through MultiInstance M...
...In this current analysis, 18 averaged measurements per experimental condition were used to assess the usefulness of three supervised classification methods in classifying infants: classical discriminant function analysis, regularized discriminant function analysis (Friedman, 1987) and support vector machines (
Vapnik, 1995
)...
Daniel Stahl
,
et al.
Novel Machine Learning Methods for ERP Analysis: A Validation From Res...
...The study of maximal marginbased learning algorithms [
1
] (or support vector machines) has become an active area of research in machine learning and data mining over the past few decades...
Jiming Peng
,
et al.
An efficient algorithm for maximal margin clustering
...Support Vector Machines (SVM) (Vapnik,
1995
; Cristianini and Taylor,
2000
; Hastie et al,
2009
) and Distance Weight Discrimination (DWD) (Marron et al,
2007
) are two commonly used large margin based classification methods...
Hanwen Huang
,
et al.
Multiclass Distance Weighted Discrimination
...The primal objective function is the sum of the loss on each training example and a regularization term that reduces the complexity of the solution (Vapnik,
1995
; Muller, Mika, Ratsch, Tsuda, & Schölkopf,
2001
)...
Ramón Huerta
,
et al.
Inhibition in Multiclass Classification
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Citations
(9780)
Drosophila Gene Expression Pattern Annotation through MultiInstance MultiLabel Learning
(
Citations: 7
)
YingXin Li
,
Shuiwang Ji
,
Sudhir Kumar
,
Jieping Ye
,
ZhiHua Zhou
Journal:
IEEE/ACM Transactions on Computational Biology and Bioinformatics  TCBB
, vol. 9, no. 1, pp. 98112, 2012
Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and SemiSupervised Learning
(
Citations: 3
)
Antonio Criminisi
,
Jamie Shotton
,
Ender Konukoglu
Published in 2012.
Novel Machine Learning Methods for ERP Analysis: A Validation From Research on Infants at Risk for Autism
(
Citations: 4
)
Daniel Stahl
,
Andrew Pickles
,
Mayada Elsabbagh
,
Mark H. Johnson
Journal:
Developmental Neuropsychology  DEVELOP NEUROPSYCHOL
, vol. 37, no. 3, pp. 274298, 2012
An efficient algorithm for maximal margin clustering
(
Citations: 2
)
Jiming Peng
,
Lopamudra Mukherjee
,
Vikas Singh
,
Dale Schuurmans
,
Linli Xu
Journal:
Journal of Global Optimization
, pp. 115, 2012
Multiclass Distance Weighted Discrimination
Hanwen Huang
,
Yufeng Liu
,
Ying Du
,
Charles M. Perou
,
D. Neil Hayes
,
Michael J. Todd
,
J. S. Marron
Journal:
Journal of Computational and Graphical Statistics  J COMPUT GRAPH STAT
, vol. justaccep, no. justaccep, 2012