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Citation(s) in
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6
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For:
Le Thi HA
, Pham Dinh T, Thiao M.
Efficient approaches for ℓ 2-ℓ 0 regularization and applications to feature selection in SVM.
APPL INTELL
2016. [DOI:
10.1007/s10489-016-0778-y
]
[
Citation(s) in
RCA
: 8
]
[
Impact Index Per Article: 1.0
]
[
Reference Citation Analysis
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[Indexed: 10/22/2022]
Number
Cited by Other Article(s)
1
Robust semi-supervised support vector machines with Laplace kernel-induced correntropy loss functions.
APPL INTELL
2020. [DOI:
10.1007/s10489-020-01865-3
]
[
Citation(s) in
RCA
: 5
]
[
Impact Index Per Article: 1.3
]
[
Reference Citation Analysis
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[Indexed: 10/23/2022]
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2
Huang Y
, Jin W, Yu Z, Li B. Supervised feature selection through Deep Neural Networks with pairwise connected structure.
Knowl Based Syst
2020. [DOI:
10.1016/j.knosys.2020.106202
]
[
Citation(s) in
RCA
: 13
]
[
Impact Index Per Article: 3.3
]
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Reference Citation Analysis
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[Indexed: 11/16/2022]
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3
The aLS-SVM based multi-task learning classifiers.
APPL INTELL
2017. [DOI:
10.1007/s10489-017-1087-9
]
[
Citation(s) in
RCA
: 14
]
[
Impact Index Per Article: 2.0
]
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[Indexed: 10/18/2022]
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4
López J
, Maldonado S, Carrasco M. A robust formulation for twin multiclass support vector machine.
APPL INTELL
2017. [DOI:
10.1007/s10489-017-0943-y
]
[
Citation(s) in
RCA
: 8
]
[
Impact Index Per Article: 1.1
]
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[Indexed: 11/25/2022]
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5
Application of binary quantum-inspired gravitational search algorithm in feature subset selection.
APPL INTELL
2017. [DOI:
10.1007/s10489-017-0894-3
]
[
Citation(s) in
RCA
: 46
]
[
Impact Index Per Article: 6.6
]
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[Indexed: 11/26/2022]
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6
Embedded heterogeneous feature selection for conjoint analysis: A SVM approach using L1 penalty.
APPL INTELL
2016. [DOI:
10.1007/s10489-016-0852-5
]
[
Citation(s) in
RCA
: 4
]
[
Impact Index Per Article: 0.5
]
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[Indexed: 10/20/2022]
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