532 citations · 1k across the 25 of their papers we have counts for
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Enhanced joint sparsity via Iterative Support Detection
Yaru Fan, Yilun Wang, Tingzhu Huang
Joint sparsity has attracted considerable attention in recent years in many fields including sparse signal recovery in compressed sensing (CS), statistics, and machine learning. Tr…
A General Stochastic Algorithmic Framework for Minimizing Expensive Black Box Objective Functions Based on Surrogate Models and Sensitivity Analysis
Yilun Wang, Christine A. Shoemaker
We are focusing on bound constrained global optimization problems, whose objective functions are computationally expensive black-box functions and have multiple local minima. The r…
Sensitivity Analysis for Computationally Expensive Models using Optimization and Objective-oriented Surrogate Approximations
Yilun Wang, Christine A. Shoemaker
In this paper, we focus on developing efficient sensitivity analysis methods for a computationally expensive objective function in the case that the minimization of it has j…
Randomized Structural Sparsity via Constrained Block Subsampling for Improved Sensitivity of Discriminative Voxel Identification
Yilun Wang, Junjie Zheng, Sheng Zhang +2
In this paper, we consider voxel selection for functional Magnetic Resonance Imaging (fMRI) brain data with the aim of finding a more complete set of probably correlated discrimina…
Truncated Nuclear Norm Minimization for Image Restoration Based On Iterative Support Detection
Yilun Wang, Xinhua Su
Recovering a large matrix from limited measurements is a challenging task arising in many real applications, such as image inpainting, compressive sensing and medical imaging, and…
Multi-stage Multi-task feature learning via adaptive threshold
Yaru Fan, Yilun Wang
Multi-task feature learning aims to identity the shared features among tasks to improve generalization. It has been shown that by minimizing non-convex learning models, a better so…