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Learning with mitigating random consistency from the accuracy measure
Jieting Wang, Yuhua Qian, Feijiang Li
Human beings may make random guesses in decision-making. Occasionally, their guesses may generate consistency with the real situation.This kind of consistency is termed random consistency. In the area of machine leaning, the randomness...
Machine Learning, 2020, 109: 2247–2281.
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成红红, 钱宇华, 胡治国, 梁吉业
识别海量变量间潜在的复杂关联关系,判断不同形式关联关系的强弱,是大数据关联关系挖掘的重要任务之一.然而,数据分布的不确定性、关联关系的多样性,使得基于分布假设的关联关系度量和基于数据驱动的非参数度量方法的适用性、准确性难以保证.
中国科学: 信息科学, 2020, 50(6): 824-844.
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李飞江, 钱宇华, 王婕婷, 梁吉业, 王文剑
数据类型和分布的复杂化导致样本间关系的不确定性增强,给有效挖掘数据的潜在类簇结构带来挑战.为降低样本关系不确定性对数据聚类带来的影响,本文将聚类集成中样本稳定性概念扩展至聚类分析中.本文从理论上分析样本稳定的合理性,并提出基于信息熵的样本稳定性度量方法.
中国科学: 信息科学, 2020, 50(8): 1239-1254.
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Tao Yan, Zhiguo Hu, Yuhua Qian, Zhiwei Qiao, Linyuan Zhang,
Multifocus image fusion techniques primarily emphasize human vision and machine perception to eval- uate an image, which often ignore depth information contained in the focus regions.
Pattern Recognition, 2020, 98, 107065.
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Latent Complete Row Space Recovery for Multi-View Subspace Clustering
Hong Tao, Chenping Hou, Yuhua Qian, Jubo Zhu, Dongyun Yi
Multi-view subspace clustering has been applied to applications such as image processing and video surveillance, and has attracted increasing attention.
IEEE Transactions on Image Processing, 2020, 29: 8083-8096
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Guide to Match: Multi-Layer Feature Matching With a Hybrid Gaussian Mixture Model
Kun Sun, Wenbing Tao, Yuhua Qian
As a fundamental yet challenging task in computer vision, finding correspondences between two sets of feature points has received extensive attention.
IEEE Transactions on Multimedia, 2020, 22(9): 2246-2261
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View-specific subspace learning and re-ranking for semi-supervised person re-identification
Jieru Jia，Qiuqi Ruan，Yi Jin，Gaoyun An，Shiming Ge.
Person re-identification (re-ID) focuses on matching the same person across non-overlapping camera views.
Pattern Recognition, 2020, 108.
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Fusing fuzzy monotonic decision trees
Jieting Wang, Yuhua Qian, Feijiang Li, Jiye Liang, Weiping Ding
Abstract—Ordinal classification is an important classification task, in which there exists a monotonic constraint between features and the decision class. In this article, we aim to develop a method of fusing ordinal decision trees with ...
IEEE Transactions on Fuzzy Systems, 2020, 28(5):887-900.
