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检索条件"机构=MIITKey Laboratory of Pattern Analysis and Machine Intelligence"
335 条 记 录,以下是241-250 订阅
排序:
Real-time human cross-race aging-related face appearance detection with deep convolution architecture
Real-time human cross-race aging-related face appearance det...
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作者: Tian, Qing Zhang, Wenqiang Mao, Junxiang Yin, Hujun School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing University of Aeronautics and Astronautics Nanjing China School of Electrical and Electronic Engineering The University of Manchester Manchester United Kingdom
Human age estimation (AE) is an emerging research topic in computer vision and machine learning and has attracted increasing amount of research due its wide potential applications. In the process of human aging, facia... 详细信息
来源: 评论
Multidimensional scaling, Sammon mapping, and Isomap: Tutorial and survey
arXiv
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arXiv 2020年
作者: Ghojogh, Benyamin Ghodsi, Ali Karray, Fakhri Crowley, Mark Department of Electrical and Computer Engineering Machine Learning Laboratory University of Waterloo WaterlooON Canada Department of Statistics and Actuarial Science David R. Cheriton School of Computer Science Data Analytics Laboratory University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada
Multidimensional Scaling (MDS) is one of the first fundamental manifold learning methods. It can be categorized into several methods, i.e., classical MDS, kernel classical MDS, metric MDS, and non-metric MDS. Sammon m... 详细信息
来源: 评论
Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey
arXiv
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arXiv 2020年
作者: Ghojogh, Benyamin Ghodsi, Ali Karray, Fakhri Crowley, Mark Department of Electrical and Computer Engineering Machine Learning Laboratory University of Waterloo WaterlooON Canada Department of Statistics and Actuarial Science David R. Cheriton School of Computer Science Data Analytics Laboratory University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada
Stochastic Neighbor Embedding (SNE) is a manifold learning and dimensionality reduction method with a probabilistic approach. In SNE, every point is consider to be the neighbor of all other points with some probabilit... 详细信息
来源: 评论
Locally linear embedding and its variants: Tutorial and survey
arXiv
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arXiv 2020年
作者: Ghojogh, Benyamin Ghodsi, Ali Karray, Fakhri Crowley, Mark Department of Electrical and Computer Engineering Machine Learning Laboratory University of Waterloo WaterlooON Canada Department of Statistics and Actuarial Science & David R. Cheriton School of Computer Science Data Analytics Laboratory University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada
This is a tutorial and survey paper for Locally Linear Embedding (LLE) and its variants. The idea of LLE is fitting the local structure of manifold in the embedding space. In this paper, we first cover LLE, kernel LLE... 详细信息
来源: 评论
Geometric interpretation of running Nyström-based kernel machines and error analysis
arXiv
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arXiv 2020年
作者: Li, Weida Liu, Mingxia Zhang, Daoqiang The College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing211106 China The Department of Radiology and BRIC University of North Carolina at Chapel Hill Chapel HillNC27599 United States
Recently, Nyström method has proved its prominence empirically and theoretically in speeding up the training of kernel machines while retaining satisfactory performances and accuracy. So far, there are several di... 详细信息
来源: 评论
Faster stochastic alternating direction method of multipliers for nonconvex optimization
arXiv
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arXiv 2020年
作者: Huang, Feihu Chen, Songcan Huang, Heng Department of Electrical & Computer Engineering University of Pittsburgh PA15261 United States College of Computer Science & Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China MIIT Key Laboratory of Pattern Analysis & Machine Intelligence JD Finance America Corporation United States
In this paper, we propose a faster stochastic alternating direction method of multipliers (ADMM) for nonconvex optimization by using a new stochastic path-integrated differential estimator (SPIDER), called as SPIDER-A... 详细信息
来源: 评论
Fisher and Kernel Fisher Discriminant analysis: Tutorial
arXiv
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arXiv 2019年
作者: Ghojogh, Benyamin Karray, Fakhri Crowley, Mark Department of Electrical and Computer Engineering Canada Machine Learning Laboratory University of Waterloo WaterlooON Canada Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada
This is a detailed tutorial paper which explains the Fisher discriminant analysis (FDA) and kernel FDA. We start with projection and reconstruction. Then, one- and multi-dimensional FDA subspaces are covered. Scatters... 详细信息
来源: 评论
ALiPy: Active learning in python
arXiv
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arXiv 2019年
作者: Tang, Ying-Peng Li, Guo-Xiang Huang, Sheng-Jun College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing211106 China
Supervised machine learning methods usually require a large set of labeled examples for model training. However, in many real applications, there are plentiful unlabeled data but limited labeled data;and the acquisiti... 详细信息
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Global expanding, local shrinking: Discriminant multi-label learning with missing labels
arXiv
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arXiv 2020年
作者: Ma, Zhongchen Chen, Songcan School of Computer Science & communications Engineering Jiangsu University Zhenjiang212013 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China MIIT Key Laboratory of Pattern Analysis & Machine Intelligence College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China
In multi-label learning, the issue of missing labels brings a major challenge. Many methods attempt to recovery missing labels by exploiting low-rank structure of label matrix. However, these methods just utilize glob... 详细信息
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Addressing the mystery of population decline of the rose-crested blue pipit in a nature preserve using data visualization
arXiv
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arXiv 2019年
作者: Ghojogh, Benyamin Crowley, Mark Karray, Fakhri Department of Electrical and Computer Engineering Machine Learning Laboratory University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada
Two main methods for exploring patterns in data are data visualization and machine learning. The former relies on humans for investigating the patterns while the latter relies on machine learning algorithms. This pape... 详细信息
来源: 评论