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Structured sparsity regularization

Structured sparsity regularization is a class of methods, and an area of research in statistical learning theory, that extend and generalize sparsity… 
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Related topics

Related topics

26 relations
Basis pursuitCompressed sensingConvex analysisConvex function

Broader (2)

Convex optimizationMachine learning

Papers overview

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Highly Cited
2019
Highly Cited
2019
Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning
The success of convolutional neural networks (CNNs) in computer vision applications has been accompanied by a significant… 
Highly Cited
2019
Highly Cited
2019
OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks
Channel pruning can significantly accelerate and compress deep neural networks. Many channel pruning works utilize structured… 
2018
2018
Semi-Supervised Spectral Clustering With Structured Sparsity Regularization
Spectral clustering (SC) is one of the most widely used clustering methods. In this letter, we extend the traditional SC with a… 
2018
2018
Structured sparsity regularization for gravitational- wave polarization reconstruction
Gravitational-wave (GW) observations with a network of more than two advanced detectors open the possibility of reconstructing… 
2018
2018
Low-rank regularized multi-view inverse-covariance estimation for visual sentiment distribution prediction
2017
2017
Heterogeneous representation learning with separable structured sparsity regularization
Motivated by real applications, heterogeneous learning has emerged as an important research area, which aims to model the… 
2016
2016
Heterogeneous Representation Learning with Structured Sparsity Regularization
Motivated by real applications, heterogeneous learning has emerged as an important research area, which aims to model the co… 
2015
2015
Cluster-sensitive Structured Correlation Analysis for Web cross-modal retrieval
2012
2012
Structured sparsity regularization approach to the EEG inverse problem
Localization of brain activity involves solving the EEG inverse problem, which is an undetermined ill-posed problem. We propose a… 
2012
2012
A General Framework of Dual Certificate Analysis for Structured Sparse Recovery Problems
This paper develops a general theoretical framework to analyze structured sparse recovery problems using the notation of dual… 
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