
Structured Graph Learning for Clustering and Semisupervised Classification
Graphs have become increasingly popular in modeling structures and inter...
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RelationGuided Representation Learning
Deep autoencoders (DAEs) have achieved great success in learning data r...
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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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Multiview Subspace Clustering via Partition Fusion
Multiview clustering is an important approach to analyze multiview dat...
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Structure Learning with Similarity Preserving
Leveraging on the underlying lowdimensional structure of data, lowrank...
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Largescale Multiview Subspace Clustering in Linear Time
A plethora of multiview subspace clustering (MVSC) methods have been pr...
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Multigraph Fusion for Multiview Spectral Clustering
A panoply of multiview clustering algorithms has been developed to deal...
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Multiple Partitions Aligned Clustering
Multiview clustering is an important yet challenging task due to the di...
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Latent Multiview SemiSupervised Classification
To explore underlying complementary information from multiple views, in ...
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Nonnegative Matrix Factorization with Local Similarity Learning
Existing nonnegative matrix factorization methods focus on learning glob...
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Clustering with Similarity Preserving
Graphbased clustering has shown promising performance in many tasks. 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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Lowrank Kernel Learning for Graphbased Clustering
Constructing the adjacency graph is fundamental to graphbased clusterin...
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Similarity Learning via Kernel Preserving Embedding
Data similarity is a key concept in many datadriven applications. Many ...
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Robust Graph Learning from Noisy Data
Learning graphs from data automatically has shown encouraging performanc...
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Selfweighted Multiple Kernel Learning for Graphbased Clustering and Semisupervised Classification
Multiple kernel learning (MKL) method is generally believed to perform b...
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Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs
Generating high fidelity identitypreserving faces has a wide range of a...
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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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A Fast Factorizationbased Approach to Robust PCA
Robust principal component analysis (RPCA) has been widely used for reco...
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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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LogDet Rank Minimization with Application to Subspace Clustering
Lowrank matrix is desired in many machine learning and computer vision ...
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Zhao Kang
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Assistant Professor at University of Electronic Science and Technology since 2017, DRA Fellow at Southern Illinois University Carbondale 20162017, PHD Student, Computer Science at Southern Illinois University Carbondale from 20132017, Research Assistant at Physics, NIST, University of Colorado at Boulder 2012, Research Assistant at Sichuan University from 20082011.