
Ensemble and Random Collaborative RepresentationBased Anomaly Detector for Hyperspectral Imagery
In recent years, hyperspectral anomaly detection (HAD) has become an act...
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Sparse PCA via l_2,pNorm Regularization for Unsupervised Feature Selection
In the field of data mining, how to deal with highdimensional data is a...
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SelfWeighted Robust LDA for Multiclass Classification with Edge Classes
Linear discriminant analysis (LDA) is a popular technique to learn the m...
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Agglomerative Neural Networks for Multiview Clustering
Conventional multiview clustering methods seek for a view consensus thr...
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Curriculum Audiovisual Learning
Associating sound and its producer in complex audiovisual scene is a cha...
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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...
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Robust and Efficient Fuzzy CMeans Clustering Constrained on Flexible Sparsity
Clustering is an effective technique in data mining to group a set of ob...
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An Iteratively Reweighted Method for Problems with SparsityInducing Norms
This work aims at solving the problems with intractable sparsityinducin...
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Robust Linear Discriminant Analysis Using Ratio Minimization of L1,2Norms
As one of the most popular linear subspace learning methods, the Linear ...
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Intrinsic Weight Learning Approach for Multiview Clustering
Exploiting different representations, or views, of the same object for b...
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Learning Feature Sparse Principal Components
Sparse PCA has shown its effectiveness in high dimensional data analysis...
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Listen to the Image
Visualtoauditory sensory substitution devices can assist the blind in ...
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Feature Learning Viewpoint of AdaBoost and a New Algorithm
The AdaBoost algorithm has the superiority of resisting overfitting. Und...
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Dense Multimodal Fusion for Hierarchically Joint Representation
Multiple modalities can provide more valuable information than single on...
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Deep LDA Hashing
The conventional supervised hashing methods based on classification do n...
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A Comprehensive Survey for Low Rank Regularization
Low rank regularization, in essence, involves introducing a low rank or ...
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Deep CoClustering for Unsupervised Audiovisual Learning
The seen birds twitter, the running cars accompany with noise, people ta...
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Regularized Singular Value Decomposition and Application to Recommender System
Singular value decomposition (SVD) is the mathematical basis of principa...
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Ranking with Adaptive Neighbors
Retrieving the most similar objects in a largescale database for a give...
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Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction
Explicitly or implicitly, most of dimensionality reduction methods need ...
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Deep Binary Reconstruction for Crossmodal Hashing
With the increasing demand of massive multimodal data storage and organi...
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From Photo Streams to Evolving Situations
Photos are becoming spontaneous, objective, and universal sources of inf...
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A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification
Linear Discriminant Analysis (LDA) is a widelyused supervised dimension...
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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...
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An Iterative Locally Linear Embedding Algorithm
Local Linear embedding (LLE) is a popular dimension reduction method. In...
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