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Asystematic review of structured sparse learning Review

Lin-bo QIAO, Bo-feng ZHANG, Jin-shu SU, Xi-cheng LU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 4, Pages 445-463 doi: 10.1631/FITEE.1601489

Abstract: Structured sparse learning encodes the structural information of the variables and has been quite successfulThese regularizations have greatly improved the efficacy of sparse learning algorithms through the useIn this article, we present a systematic review of structured sparse learning including ideas, formulationssparse learning problems.In experiments, we present applications in unsupervised learning, for structured signal recovery and

Keywords： Sparse learning Structured sparse learning Structured regularization

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Laplacian sparse dictionary learning for image classification based on sparse representation Article

Fang LI, Jia SHENG, San-yuan ZHANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11, Pages 1795-1805 doi: 10.1631/FITEE.1600039

Abstract: Sparse representation is a mathematical model for data representation that has proved to be a powerfultool for solving problems in various fields such as pattern recognition, machine learning, and computerAs one of the building blocks of the sparse representation method, dictionary learning plays an importantdictionary (LSD) learning.Our method is based on manifold learning and double sparsity.

Keywords： Sparse representation Laplacian regularizer Dictionary learning Double sparsity Manifold

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Unsupervised feature selection via joint local learning and group sparse regression Regular Papers

Yue WU, Can WANG, Yue-qing ZHANG, Jia-jun BU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 4, Pages 538-553 doi: 10.1631/FITEE.1700804

Abstract: By selecting meaningful feature subsets, the performance of learning algorithms can be effectively improvedTo address this issue, we propose a novel unsupervised feature selection algorithm via joint local learningand group sparse regression (JLLGSR).JLLGSR incorporates local learning based clustering with group sparsity regularized regression in a singleformulation, and seeks features that respect both the manifold structure and group sparse structure

Keywords： Unsupervised Local learning Group sparse regression Feature selection

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Efficient scheme of low-dose CT reconstruction using TV minimization with an adaptive stopping strategy and sparsedictionary learning for post-processing Article

Yong DING, Tuo HU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 12, Pages 2001-2008 doi: 10.1631/FITEE.1700287

Abstract: imaging, we propose a promising reconstruction scheme which combines total-variation minimization and sparsedictionary learning to enhance the reconstruction performance, and properly schedule them with an adaptive

Keywords： Low-dose computed tomography (CT) CT imaging Total variation Sparse dictionary learning

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Robust object tracking with RGBD-based sparse learning Article

Zi-ang MA, Zhi-yu XIANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7, Pages 989-1001 doi: 10.1631/FITEE.1601338

Abstract: In this paper, a novel RGBD and sparse learning based tracker is proposed.The range data is integrated into the sparse learning framework in three respects.demonstrate that the proposed tracker outperforms the state-of-the-art tracking algorithms, including both sparselearning and RGBD based methods.

Keywords： Object tracking Sparse learning Depth view Occlusion templates Occlusion detection

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Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12, Pages 1046-1058 doi: 10.1631/FITEE.1500085

Abstract: With the development of face recognition using sparse representation based classification (SRC), manyHowever, when the dictionary is large and the representation is sparse, only a small proportion of theIn this paper, we employ a metric learning approach which helps find the active elements correctly by

Keywords： Face recognition Sparse representation Manifold structure Metric learning Subset selection

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Multiple fault separation and detection by joint subspace learning for the health assessment of wind

Zhaohui DU, Xuefeng CHEN, Han ZHANG, Yanyang ZI, Ruqiang YAN

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3, Pages 333-347 doi: 10.1007/s11465-017-0435-0

Abstract: Thus, this paper presents a joint subspace learning-based multiple fault detection (JSL-MFD) technique

Keywords： joint subspace learning multiple fault diagnosis sparse decomposition theory coupling feature separation

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Kernel sparse representation for MRI image analysis in automatic brain tumor segmentation None

Ji-jun TONG, Peng ZHANG, Yu-xiang WENG, Dan-hua ZHU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4, Pages 471-480 doi: 10.1631/FITEE.1620342

Abstract: We propose a fully automatic brain tumor segmentation method based on kernel sparse coding.In this method, MRI images are pre-processed first to reduce the noise, and then kernel dictionary learningSparse coding is performed on the feature vectors extracted from the original MRI images, which are aA kernel-clustering algorithm based on dictionary learning is developed to code the voxels.

Keywords： Brain tumor segmentation Kernel method Sparse coding Dictionary learning

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Building trust networks in the absence of trust relations Article

Xin WANG, Ying WANG, Jian-hua GUO

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10, Pages 1591-1600 doi: 10.1631/FITEE.1601341

Abstract: User-specified trust relations are often very sparse and dynamic, making them difficult to accuratelyIn this study, we investigate whether we can predict trust relations via a sparse learning model, and

Keywords： Trust network Sparse learning Homophily effect Interaction behaviors

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Sparse fast Clifford Fourier transform Article

Rui WANG, Yi-xuan ZHOU, Yan-liang JIN, Wen-ming CAO

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8, Pages 1131-1141 doi: 10.1631/FITEE.1500452

Abstract: The sparse fast Fourier transform (sFFT) theory deals with the big data problem by using input data selectivelyThis has inspired us to create a new algorithm called sparse fast CFT (SFCFT), which can greatly improve

Keywords： Sparse fast Fourier transform (sFFT) Clifford Fourier transform (CFT) Sparse fast Clifford Fourier

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Non-convex sparse optimization-based impact force identification with limited vibration measurements

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 3, doi: 10.1007/s11465-023-0762-2

Abstract: mn> regularization method often struggles to generate sparseMJX-TeXAtom-ORD">ℓ1 sparseTo alleviate such limitations, a novel non-convex sparse regularization method that uses the non-convexrealize simultaneous impact localization and time history reconstruction with an under-determined, sparse

Keywords： impact force identification inverse problem sparse regularization under-determined condition alternating

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Water quality soft-sensor prediction in anaerobic process using deep neural network optimized by Tree-structured

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1667-3

Abstract:

● Hybrid deep-learning model is proposed for water quality prediction

Keywords： Water quality prediction Soft-sensor Anaerobic process Tree-structured Parzen Estimator

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Computational design of structured chemical products

Faheem Mushtaq, Xiang Zhang, Ka Y. Fung, Ka M. Ng

Frontiers of Chemical Science and Engineering 2021, Volume 15, Issue 5, Pages 1033-1049 doi: 10.1007/s11705-020-2002-1

Abstract: proposed performance, ingredients, structure, and manufacturing process framework for the design of structured

Keywords： product design performance ingredients structure manufacturing process framework structured chemical

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Uncertainty propagation analysis by an extended sparse grid technique

X. Y. JIA, C. JIANG, C. M. FU, B. Y. NI, C. S. WANG, M. H. PING

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 1, Pages 33-46 doi: 10.1007/s11465-018-0514-x

Abstract: In this paper, an uncertainty propagation analysis method is developed based on an extended sparse gridSubsequently, within the sparse grid numerical integration framework, the statistical moments of the

Keywords： uncertainty propagation analysis extended sparse grid maximum entropy principle extended Gauss integration

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Efficient and selective electro-reduction of nitrobenzene by the nano-structured Cu catalyst prepared

Yali CHEN,Lu XIONG,Weikang WANG,Xing ZHANG,Hanqing YU

Frontiers of Environmental Science & Engineering 2015, Volume 9, Issue 5, Pages 897-904 doi: 10.1007/s11783-015-0782-1

Abstract: The dendritic nano-structured Cu catalysts obtained at high applied voltages exhibited an excellent efficiencyThe fabricated nano-structured Cu catalysts also exhibited good stability.This work provides a facile way to prepare highly efficient, cost-effective, and stable nano-structured

Keywords： nitrobenzene nano-structured Cu electro-reduction voltage-dependent electrodeposition high selectivity

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Title Author Date Type Operation

Asystematic review of structured sparse learning

Lin-bo QIAO, Bo-feng ZHANG, Jin-shu SU, Xi-cheng LU

Journal Article

Laplacian sparse dictionary learning for image classification based on sparse representation

Fang LI, Jia SHENG, San-yuan ZHANG

Journal Article

Unsupervised feature selection via joint local learning and group sparse regression

Yue WU, Can WANG, Yue-qing ZHANG, Jia-jun BU

Journal Article

Efficient scheme of low-dose CT reconstruction using TV minimization with an adaptive stopping strategy and sparsedictionary learning for post-processing

Yong DING, Tuo HU

Journal Article

Robust object tracking with RGBD-based sparse learning

Zi-ang MA, Zhi-yu XIANG

Journal Article

Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Journal Article

Multiple fault separation and detection by joint subspace learning for the health assessment of wind

Zhaohui DU, Xuefeng CHEN, Han ZHANG, Yanyang ZI, Ruqiang YAN

Journal Article

Kernel sparse representation for MRI image analysis in automatic brain tumor segmentation