Feiping Nie

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Ensemble and Random Collaborative Representation-Based Anomaly Detector for Hyperspectral Imagery

In recent years, hyperspectral anomaly detection (HAD) has become an act...
01/06/2021 ∙ by Rong Wang, et al. ∙ 8 ∙ share

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Sparse PCA via l_2,p-Norm Regularization for Unsupervised Feature Selection

In the field of data mining, how to deal with high-dimensional data is a...
12/29/2020 ∙ by Zhengxin Li, et al. ∙ 0 ∙ share

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Self-Weighted Robust LDA for Multiclass Classification with Edge Classes

Linear discriminant analysis (LDA) is a popular technique to learn the m...
09/24/2020 ∙ by Caixia Yan, et al. ∙ 12 ∙ share

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Agglomerative Neural Networks for Multi-view Clustering

Conventional multi-view clustering methods seek for a view consensus thr...
05/12/2020 ∙ by Zhe Liu, et al. ∙ 0 ∙ share

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Curriculum Audiovisual Learning

Associating sound and its producer in complex audiovisual scene is a cha...
01/26/2020 ∙ by Di Hu, et al. ∙ 6 ∙ share

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Supervised feature selection with orthogonal regression and feature weighting

Effective features can improve the performance of a model, which can thu...
10/09/2019 ∙ by Xia Wu, et al. ∙ 0 ∙ share

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Robust and Efficient Fuzzy C-Means Clustering Constrained on Flexible Sparsity

Clustering is an effective technique in data mining to group a set of ob...
08/19/2019 ∙ by Jinglin Xu, et al. ∙ 1 ∙ share

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An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms

This work aims at solving the problems with intractable sparsity-inducin...
07/02/2019 ∙ by Feiping Nie, et al. ∙ 0 ∙ share

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Robust Linear Discriminant Analysis Using Ratio Minimization of L1,2-Norms

As one of the most popular linear subspace learning methods, the Linear ...
06/29/2019 ∙ by Feiping Nie, et al. ∙ 0 ∙ share

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Intrinsic Weight Learning Approach for Multi-view Clustering

Exploiting different representations, or views, of the same object for b...
06/21/2019 ∙ by Feiping Nie, et al. ∙ 0 ∙ share

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Learning Feature Sparse Principal Components

Sparse PCA has shown its effectiveness in high dimensional data analysis...
04/23/2019 ∙ by Lai Tian, et al. ∙ 0 ∙ share

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Listen to the Image

Visual-to-auditory sensory substitution devices can assist the blind in ...
04/19/2019 ∙ by Di Hu, et al. ∙ 0 ∙ share

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Feature Learning Viewpoint of AdaBoost and a New Algorithm

The AdaBoost algorithm has the superiority of resisting overfitting. Und...
04/08/2019 ∙ by Fei Wang, et al. ∙ 0 ∙ share

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Dense Multimodal Fusion for Hierarchically Joint Representation

Multiple modalities can provide more valuable information than single on...
10/08/2018 ∙ by Di Hu, et al. ∙ 0 ∙ share

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Deep LDA Hashing

The conventional supervised hashing methods based on classification do n...
10/08/2018 ∙ by Di Hu, et al. ∙ 0 ∙ share

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A Comprehensive Survey for Low Rank Regularization

Low rank regularization, in essence, involves introducing a low rank or ...
08/14/2018 ∙ by Zhanxuan Hu, et al. ∙ 0 ∙ share

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Deep Co-Clustering for Unsupervised Audiovisual Learning

The seen birds twitter, the running cars accompany with noise, people ta...
07/09/2018 ∙ by Di Hu, et al. ∙ 2 ∙ share

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Regularized Singular Value Decomposition and Application to Recommender System

Singular value decomposition (SVD) is the mathematical basis of principa...
04/13/2018 ∙ by Shuai Zheng, et al. ∙ 0 ∙ share

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Ranking with Adaptive Neighbors

Retrieving the most similar objects in a large-scale database for a give...
03/14/2018 ∙ by Muge Li, et al. ∙ 0 ∙ share

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Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction

Explicitly or implicitly, most of dimensionality reduction methods need ...
09/09/2017 ∙ by Yanwei Pang, et al. ∙ 0 ∙ share

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Deep Binary Reconstruction for Cross-modal Hashing

With the increasing demand of massive multimodal data storage and organi...
08/17/2017 ∙ by Xuelong Li, et al. ∙ 0 ∙ share

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From Photo Streams to Evolving Situations

Photos are becoming spontaneous, objective, and universal sources of inf...
02/20/2017 ∙ by Mengfan Tang, et al. ∙ 0 ∙ share

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A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification

Linear Discriminant Analysis (LDA) is a widely-used supervised dimension...
10/14/2016 ∙ by Shuai Zheng, et al. ∙ 0 ∙ share

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Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning

Domain adaptation problems arise in a variety of applications, where a t...
09/05/2015 ∙ by Wenhao Jiang, et al. ∙ 0 ∙ share

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An Iterative Locally Linear Embedding Algorithm

Local Linear embedding (LLE) is a popular dimension reduction method. In...
06/27/2012 ∙ by Deguang Kong, et al. ∙ 0 ∙ share

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Feiping Nie

Featured Co-authors

Wei Liu

Dong Wang

Fei Wang

Qi Wang

Zheng Wang

Jing Li

Xuelong Li

Lina Yao

Heng Huang

Zhe Liu

Wei Feng

Ensemble and Random Collaborative Representation-Based Anomaly Detector for Hyperspectral Imagery

Sparse PCA via l_2,p-Norm Regularization for Unsupervised Feature Selection

Self-Weighted Robust LDA for Multiclass Classification with Edge Classes

Agglomerative Neural Networks for Multi-view Clustering

Curriculum Audiovisual Learning

Supervised feature selection with orthogonal regression and feature weighting

Robust and Efficient Fuzzy C-Means Clustering Constrained on Flexible Sparsity

An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms

Robust Linear Discriminant Analysis Using Ratio Minimization of L1,2-Norms

Intrinsic Weight Learning Approach for Multi-view Clustering

Learning Feature Sparse Principal Components

Listen to the Image

Feature Learning Viewpoint of AdaBoost and a New Algorithm

Dense Multimodal Fusion for Hierarchically Joint Representation

Deep LDA Hashing

A Comprehensive Survey for Low Rank Regularization

Deep Co-Clustering for Unsupervised Audiovisual Learning

Regularized Singular Value Decomposition and Application to Recommender System

Ranking with Adaptive Neighbors

Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction

Deep Binary Reconstruction for Cross-modal Hashing

From Photo Streams to Evolving Situations

A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification

Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning

An Iterative Locally Linear Embedding Algorithm