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05/21/2023
Joint Feature and Differentiable k-NN Graph Learning using Dirichlet Energy
Feature selection (FS) plays an important role in machine learning, whic...
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05/12/2023
AGFormer: Efficient Graph Representation with Anchor-Graph Transformer
To alleviate the local receptive issue of GCN, Transformers have been ex...
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12/07/2022
On the Global Solution of Soft k-Means
This paper presents an algorithm to solve the Soft k-Means problem globa...
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11/03/2022
Unified Multi-View Orthonormal Non-Negative Graph Based Clustering Framework
Spectral clustering is an effective methodology for unsupervised learnin...
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04/11/2022
A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challenges
Legal judgment prediction (LJP) applies Natural Language Processing (NLP...
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01/31/2022
Compactness Score: A Fast Filter Method for Unsupervised Feature Selection
For feature engineering, feature selection seems to be an important rese...
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01/20/2022
Adaptive neighborhood Metric learning
In this paper, we reveal that metric learning would suffer from serious ...
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12/09/2021
New Tight Relaxations of Rank Minimization for Multi-Task Learning
Multi-task learning has been observed by many researchers, which suppose...
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01/06/2021
Ensemble and Random Collaborative Representation-Based Anomaly Detector for Hyperspectral Imagery
In recent years, hyperspectral anomaly detection (HAD) has become an act...
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12/29/2020
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...
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09/24/2020
Self-Weighted Robust LDA for Multiclass Classification with Edge Classes
Linear discriminant analysis (LDA) is a popular technique to learn the m...
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05/12/2020
Agglomerative Neural Networks for Multi-view Clustering
Conventional multi-view clustering methods seek for a view consensus thr...
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01/26/2020
Curriculum Audiovisual Learning
Associating sound and its producer in complex audiovisual scene is a cha...
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10/09/2019
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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08/19/2019
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...
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07/02/2019
An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms
This work aims at solving the problems with intractable sparsity-inducin...
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06/29/2019
Robust Linear Discriminant Analysis Using Ratio Minimization of L1,2-Norms
As one of the most popular linear subspace learning methods, the Linear ...
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06/21/2019
Intrinsic Weight Learning Approach for Multi-view Clustering
Exploiting different representations, or views, of the same object for b...
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04/23/2019
Learning Feature Sparse Principal Components
Sparse PCA has shown its effectiveness in high dimensional data analysis...
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04/19/2019
Listen to the Image
Visual-to-auditory sensory substitution devices can assist the blind in ...
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04/08/2019
Feature Learning Viewpoint of AdaBoost and a New Algorithm
The AdaBoost algorithm has the superiority of resisting overfitting. Und...
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10/08/2018
Dense Multimodal Fusion for Hierarchically Joint Representation
Multiple modalities can provide more valuable information than single on...
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10/08/2018
Deep LDA Hashing
The conventional supervised hashing methods based on classification do n...
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08/14/2018
A Comprehensive Survey for Low Rank Regularization
Low rank regularization, in essence, involves introducing a low rank or ...
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07/09/2018
Deep Co-Clustering for Unsupervised Audiovisual Learning
The seen birds twitter, the running cars accompany with noise, people ta...
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04/13/2018
Regularized Singular Value Decomposition and Application to Recommender System
Singular value decomposition (SVD) is the mathematical basis of principa...
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03/14/2018
Ranking with Adaptive Neighbors
Retrieving the most similar objects in a large-scale database for a give...
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09/09/2017
Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction
Explicitly or implicitly, most of dimensionality reduction methods need ...
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08/17/2017
Deep Binary Reconstruction for Cross-modal Hashing
With the increasing demand of massive multimodal data storage and organi...
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02/20/2017
From Photo Streams to Evolving Situations
Photos are becoming spontaneous, objective, and universal sources of inf...
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10/14/2016
A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification
Linear Discriminant Analysis (LDA) is a widely-used supervised dimension...
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09/05/2015
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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06/27/2012