398 citations · 2k across the 69 of their papers we have counts for
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Greedy metrics in orthogonal greedy learning
Lin Xu, Shaobo Lin, Jinshan Zeng +1
Orthogonal greedy learning (OGL) is a stepwise learning scheme that adds a new atom from a dictionary via the steepest gradient descent and build the estimator via orthogonal proje…
On parallel multisplitting block iterative methods for linear systems arising in the numerical solution of Euler equations
Cheng-yi Zhang, Shuanghua Luo, Zongben Xu
The paper studies the convergence of some parallel multisplitting block iterative methods for the solution of linear systems arising in the numerical solution of Euler equations. S…
Learning and approximation capability of orthogonal super greedy algorithm
Jian Fang, Shaobo Lin, Zongben Xu
We consider the approximation capability of orthogonal super greedy algorithms (OSGA) and its applications in supervised learning. OSGA is concerned with selecting more than one at…
A Cyclic Coordinate Descent Algorithm for lq Regularization
Jinshan Zeng, Zhimin Peng, Shaobo Lin +1
In recent studies on sparse modeling, () regularization has received considerable attention due to its superiorities on sparsity-inducing and bias reduction over the $…
Linear Convergence of Adaptively Iterative Thresholding Algorithms for Compressed Sensing
Yu Wang, Jinshan Zeng, Zhimin Peng +2
This paper studies the convergence of the adaptively iterative thresholding (AIT) algorithm for compressed sensing. We first introduce a generalized restricted isometry property (g…
On the Optimal Solution of Weighted Nuclear Norm Minimization
Qi Xie, Deyu Meng, Shuhang Gu +4
In recent years, the nuclear norm minimization (NNM) problem has been attracting much attention in computer vision and machine learning. The NNM problem is capitalized on its conve…
Sparse K-Means with Penalty for High-Dimensional Data Clustering
Xiangyu Chang, Yu Wang, Rongjian Li +1
Sparse clustering, which aims to find a proper partition of an extremely high-dimensional data set with redundant noise features, has been attracted more and more interests in rece…
Categorization Axioms for Clustering Results
Jian Yu, Zongben Xu
Cluster analysis has attracted more and more attention in the field of machine learning and data mining. Numerous clustering algorithms have been proposed and are being developed d…
Sparse Regularization: Convergence Of Iterative Jumping Thresholding Algorithm
Jinshan Zeng, Shaobo Lin, Zongben Xu
In recent studies on sparse modeling, non-convex penalties have received considerable attentions due to their superiorities on sparsity-inducing over the convex counterparts. Compa…
Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part II)
Shaobo Lin, Xia Liu, Jian Fang +1
An extreme learning machine (ELM) can be regarded as a two stage feed-forward neural network (FNN) learning system which randomly assigns the connections with and within hidden neu…