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Efficient and robust kernel learning with class-wise privileged information for pattern classification

delete2026-03-19
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PRE
AI
J
Jingjing Tang
Q
Qiao Gou
S
Saiji Fu
K
Kun Zhao *
T
Tianyi Dong
田英杰 (Yingjie Tian)
DOI:10.1016/j.patcog.2026.113522delete
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Abstract

Abstract

En 中文
• CPSVM is an efficient single-stage kernel learning framework with class-wise PI. • CPSVM flexibly supports both discrete and continuous forms of privileged information. • A rescaled hinge loss is introduced to improve robustness against noisy information. • We theoretically analyze the convergence and generalization properties of CPSVM. • CPSVM achieves a favorable trade-off between predictive performance and efficiency.
Keywords:
CPSVM
privileged information
kernel learning
class-wise
robustness

Journal

Pattern Recognition cover
Pattern Recognition
IF:
7.6
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1.3W
Citations:
4.5W

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