
Topk Regularization for Supervised Feature Selection
Feature selection identifies subsets of informative features and reduces...
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Deepened Graph AutoEncoders Help Stabilize and Enhance Link Prediction
Graph neural networks have been used for a variety of learning tasks, su...
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Adaptive Weighted Discriminator for Training Generative Adversarial Networks
Generative adversarial network (GAN) has become one of the most importan...
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Kernel TwoDimensional Ridge Regression for Subspace Clustering
Subspace clustering methods have been widely studied recently. When the ...
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Fractal Autoencoders for Feature Selection
Feature selection reduces the dimensionality of data by identifying a su...
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A Uniformly Stable Algorithm For Unsupervised Feature Selection
Highdimensional data presents challenges for data management. Feature s...
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Structured Graph Learning for Clustering and Semisupervised Classification
Graphs have become increasingly popular in modeling structures and inter...
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TwoDimensional SemiNonnegative Matrix Factorization for Clustering
In this paper, we propose a new SemiNonnegative Matrix Factorization me...
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MIMO Transmission through Reconfigurable Intelligent Surface: System Design, Analysis, and Implementation
Reconfigurable intelligent surface (RIS) is a new paradigm that has grea...
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Wireless Communications with Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement
Reconfigurable intelligent surfaces (RISs) comprised of tunable unit cel...
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Nonnegative Matrix Factorization with Local Similarity Learning
Existing nonnegative matrix factorization methods focus on learning glob...
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Automated Classification of Seizures against Nonseizures: A Deep Learning Approach
In current clinical practice, electroencephalograms (EEG) are reviewed a...
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RESPCA: A Scalable Approach to Recovering Lowrank Matrices
Robust principal component analysis (RPCA) has drawn significant attenti...
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Discriminative Regression Machine: A Classifier for HighDimensional Data or Imbalanced Data
We introduce a discriminative regression approach to supervised classifi...
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A Novel Independent RNN Approach to Classification of Seizures against Nonseizures
In current clinical practices, electroencephalograms (EEG) are reviewed ...
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Lie Group AutoEncoder
In this paper, we propose an autoencoder based generative neural networ...
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Wireless Communications with Programmable Metasurface: Transceiver Design and Experimental Results
Metasurfaces have drawn significant attentions due to their superior cap...
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Adaptive Edge Features Guided Graph Attention Networks
Edge features contain important information about graphs. However, curre...
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Controlling spectral energies of all harmonics in programmable way using timedomain digital coding metasurface
Modern wireless communication is one of the most important information t...
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Unified Spectral Clustering with Optimal Graph
Spectral clustering has found extensive use in many areas. Most traditio...
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Twin Learning for Similarity and Clustering: A Unified Kernel Approach
Many similaritybased clustering methods work in two separate steps incl...
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TopN Recommendation on Graphs
Recommender systems play an increasingly important role in online applic...
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TopN Recommendation with Novel Rank Approximation
The importance of accurate recommender systems has been widely recognize...
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TopN Recommender System via Matrix Completion
TopN recommender systems have been investigated widely both in industry...
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Robust PCA via Nonconvex Rank Approximation
Numerous applications in data mining and machine learning require recove...
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Robust Subspace Clustering via Tighter Rank Approximation
Matrix rank minimization problem is in general NPhard. The nuclear norm...
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Robust Subspace Clustering via Smoothed Rank Approximation
Matrix rank minimizing subject to affine constraints arises in many appl...
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Qiang Cheng
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