Representative Selection with Structured Sparsity by Wang, Hongxing, Kawahara, Yoshinobu, Weng, Chaoqun, Yuan, Junsong

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Reconciliation of statistical and spatial sparsity for robust visual classification by Cheng, Hao, Yap, Kim-Hui, Wen, Bihan

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Fast Bayesian inference of Sparse Networks with automatic sparsity determination by Yu, Hang, Wu, Songwei, Xin, Luyin, Dauwels, Justin

“…It is therefore tempting to develop tuning-free algorithms that can determine the sparsity of the graph adaptively from the observed data in an automatic fashion. …”
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Nonlocal structured sparsity regularization modeling for hyperspectral image denoising by Zha, Zhiyuan, Wen, Bihan, Yuan, Xin, Zhang, Jiachao, Zhou, Jiantao, Lu, Yilong, Zhu, Ce

“…To address these limitations, this article proposes a novel nonlocal structured sparsity regularization (NLSSR) approach for HSI denoising. …”
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Block-sparsity-aware LMS algorithm for network echo cancellation by Wei, Ye, Zhang, Yonggang, Wang, Chengcheng

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Image restoration via reconciliation of group sparsity and low-rank models by Zha, Zhiyuan, Wen, Bihan, Yuan, Xin, Zhou, Jiantao, Zhu, Ce

“…Image nonlocal self-similarity (NSS) property has been widely exploited via various sparsity models such as joint sparsity (JS) and group sparse coding (GSC). …”
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Primary-ambient extraction using ambient phase estimation with a sparsity constraint by He, Jianjun, Gan, Woon-Seng, Tan, Ee-Leng

“…In this Letter, we propose a novel PAE approach by estimating the ambient phase with a sparsity constraint (APES). This approach exploits the equal magnitude of the uncorrelated ambient components in the two channels of a stereo signal and reformulates the PAE problem as an ambient phase estimation problem, which is then solved using the criterion that the primary component is sparse. …”
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ACSL : adaptive correlation-driven sparsity learning for deep neural network compression by He, Wei, Wu, Meiqing, Lam, Siew-Kei

“…Next, we leverage these inter-dependencies to induce sparsity into the channels with the introduced adaptive penalty strength. …”
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Sparsity-based beamforming to enhance two-dimensional linear-array photoacoustic tomography by Mozaffarzadeh, Moein, Periyasamy, Vijitha, Paridar, Roya, Pramanik, Manojit, Mehrmohammadi, Mohammad, Orooji, Mahdi

“…We define a forward/backward problem of the beamforming and solve the inverse problem using a sparse constraint added to the model which forces the sparsity of the output beamformed data. It is shown that the proposed Sparse beamforming (SB) method is robust against noise due to the sparsity nature of the problem. …”
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Non-uniform illumination underwater image restoration via illumination channel sparsity prior by Hou, Guojia, Li, Nan, Zhuang, Peixian, Li, Kunqian, Sun, Haihan, Li, Chongyi

“…To this end, we develop an illumination channel sparsity prior (ICSP) guided variational framework for non-uniform Illumination underwater image restoration. …”
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The Race to Improve Radar Imagery: An overview of recent progress in statistical sparsity-based techniques by Zhao, Lifan, Wang, Lu, Yang, Lei, Zoubir, Abdelhak M., Bi, Guoan

“…More recent developments in compressed sensing (CS) suggest that statistical sparsity can lead to further performance benefits by imposing sparsity as a statistical prior on the considered signal. …”
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Sparsity-based image inpainting detection via canonical correlation analysis with low-rank constraints by Jin, Xiao, Su, Yuting, Zou, Liang, Wang, Yongwei, Jing, Peiguang, Wang, Z. Jane

“…Compared with other types of inpainting, sparsity-based inpainting exploits more general prior knowledge and has a broader application scope. …”
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Sparse sensor selection for distributed systems: an l1-relaxation approach by Zhong, Yuxing, Yang, Nachuan, Huang, Lingying, Shi, Guodong, Shi, Ling

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Array-based underwater acoustic target classification with spectrum reconstruction based on joint sparsity and frequency shift invariant feature by Lu, Chenxiang, Zeng, Xiangyang, Wang, Qiang, Wang, Lu, Jin, Anqi

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Primary-Ambient Extraction Using Ambient Spectrum Estimation for Immersive Spatial Audio Reproduction by He, Jianjun, Gan, Woon-Seng, Tan, Ee-Leng

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An autofocus technique for high-resolution inverse synthetic aperture radar imagery by Zhao, Lifan, Wang, Lu, Yang, Lei, Bi, Guoan

“…For inverse synthetic aperture radar imagery, the inherent sparsity of the scatterers in the range-Doppler domain has been exploited to achieve a high-resolution range profile or Doppler spectrum. …”
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Robust frequency-hopping spectrum estimation based on sparse bayesian method by Wang, Lu, Zhao, Lifan, Bi, Guoan, Zhang, Liren, Zhang, Haijian

“…Inspired by the sparse Bayesian learning algorithm, the problem is formulated hierarchically to induce sparsity. In addition to the sparsity, the hopping pattern is exploited via temporal-aware clustering by exerting a dependent Dirichlet process prior over the latent parametric space. …”
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FAT: an in-memory accelerator with fast addition for ternary weight neural networks by Zhu, Shien, Duong, Luan H. K., Chen, Hui, Liu, Di, Liu, Weichen

“…However, though TWNs have higher accuracy and better sparsity than BWNs, IMC acceleration for TWNs has limited research. …”
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Abnormal event detection in crowded scenes using sparse representation by Cong, Yang, Yuan, Junsong, Liu, Ji

“…To condense the over-completed normal bases into a compact dictionary, a novel dictionary selection method with group sparsity constraint is designed, which can be solved by standard convex optimization. …”
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Sparse Sequential Generalization of K-means for dictionary training on noisy signals by Sahoo, Sujit Kumar, Makur, Anamitra

“…However, a fixed sparsity can become too rigid to adapt to the training samples. …”
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