Oct 9, 2018 · In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, ...
A Family of Maximum Margin Criterion for Adaptive Learning - SpringerLink
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Nov 18, 2018 · To address high-dimensional problem of original data, there has been a common sense that reaches the eigen-decomposition of scatter matrices ...
A novel approach to adaptive matching of kernel means is proposed, and selected data with high importance are adopted to achieve calculation efficiency with ...
Oct 9, 2018 · In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, ...
With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D MMC, are designed to make adaptive learning applicable.
With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D MMC, are designed to make adaptive learning applicable.
A Family of Maximum Margin Criterion for Adaptive Learning. Resource URI: https://dblp.l3s.de/d2r/resource/publications/journals/corr/abs-1810-04064. Home ...
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2018. Miao Cheng, Zunren Liu, Hongwei Zou, Ah Chung Tsoi, A Family of Maximum Margin Criterion for Adaptive Learning. in Proc. International Conference on ...
A Family of Maximum Margin Criterion for Adaptive Learning ... In recent years, pattern analysis plays an important role in data mining and recognition, and many ...
In this paper, we propose a weighted maximum margin criterion to optimize the data-dependent kernel, which makes the minority class more clustered in the ...
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