Online multikernel learning based on a triple-norm regularizer for semantic image classification

DOI10.1155/2015/346496zbMath1394.68293OpenAlexW2121792406WikidataQ59118086 ScholiaQ59118086MaRDI QIDQ1665404

Lianwen Jin, Yunyu Li, Shuangping Huang

Publication date: 27 August 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/346496

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18)

Uses Software

• SHOGUN
• AdaBoost.MH
• MNIST

Cites Work

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• Kernel methods in machine learning
• A decision-theoretic generalization of on-line learning and an application to boosting
• Online multiple kernel classification
• Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning
• Multiple Kernel Learning for Sparse Representation-Based Classification
• Online Multiple Kernel Learning: Algorithms and Mistake Bounds
• Modeling the shape of the scene: A holistic representation of the spatial envelope