Ensemble Neighborhood Search (ENS) for biclustering of gene expression microarray data and single cell RNA sequencing data by Bhawani Sankar Biswal, Anjali Mohapatra, Swati Vipsita

“…Also this framework preforms effectively on high sparsity scRNA-seq data where most of the algorithms fail to do so as these datasets contain massive zeros within. …”
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IT-PMF: A Novel Community E-Commerce Recommendation Method Based on Implicit Trust by Jun Wu, Xinyu Song, Xiaxia Niu, Li Shi, Lu Gao, Liping Geng, Dan Wang, Dongkui Zhang

“…It is well-known that data sparsity and cold start are two of the open problems in recommendation system research. …”
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POI Recommendation Method of Neural Matrix Factorization Integrating Auxiliary Attribute Information by Xiaoyan Li, Shenghua Xu, Tao Jiang, Yong Wang, Yu Ma, Yiming Liu

“…In addition, to alleviate the data-sparsity problem, current methods primarily introduce the auxiliary information of users and POIs. …”
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Row-Wise Product-Based Sparse Matrix Multiplication Hardware Accelerator With Optimal Load Balancing by Jong Hun Lee, Beomjin Park, Joonho Kong, Arslan Munir

“…These workloads often exhibit high sparsity in data, which means a large portion of the elements in the data are zero-valued elements. …”
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A Survey on Recommendation Methods Based on Social Relationships by Rui Chen, Kangning Pang, Min Huang, Hui Liang, Shizheng Zhang, Lei Zhang, Pu Li, Zhengwei Xia, Jianwei Zhang, Xiangjie Kong

“…To solve the problems of cold start and sparsity in RSs, many recommendation algorithms are constantly being proposed. …”
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Automated Parameter Selection for Accelerated MRI Reconstruction via Low-Rank Modeling of Local k-Space Neighborhoods by Efe Ilicak, Emine Ulku Saritas, Tolga Çukur

“…Here, we propose a parameter tuning strategy to automate hybrid parallel imaging (PI) – compressed sensing (CS) reconstructions via low-rank modeling of local k-space neighborhoods (LORAKS) supplemented with sparsity regularization in wavelet and total variation (TV) domains. …”
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Remote Sensing Image of The Landsat 8–9 Compressive Sensing via Non-Local Low-Rank Regularization with the Laplace Function by Guibing Li, Weidong Jin, Jiaqing Miao, Ying Tan, Yingling Li, Weixuan Zhang, Liang Li

“…Nevertheless, most CS algorithms focus on the sparsity of an RSI and ignore its low-rank (LR) nature. …”
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An Efficient Sinogram Domain Fully Convolutional Interpolation Network for Sparse-View Computed Tomography Reconstruction by Fupei Guo, Bo Yang, Hao Feng, Wenfeng Zheng, Lirong Yin, Zhengtong Yin, Chao Liu

“…It is shown that despite the computational simplicity of the proposed model, its reconstruction performance at lower sparsity levels (1/2 and 1/4 radiation dose) is comparable to that of the sophisticated baseline models and shows some advantages at higher sparsity levels (1/8 and 1/15 radiation dose). …”
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An Affine Precoded Superimposed Pilot-Based mmWave MIMO-OFDM ISAC System by Awadhesh Gupta, Meesam Jafri, Suraj Srivastava, Aditya K. Jagannatham, Lajos Hanzo

“…The sparse Bayesian learning (BL)-based joint-BL (J-BL) technique is developed for this system that efficiently exploits the sparsity of the radar scattering environment. Next, a group sparse BL (G-BL) technique is also derived that exploits the group sparsity across subcarriers for the estimation of the wireless beamspace channel vector, which outperforms the competing techniques, including conventional sparse BL. …”
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A malware propagation prediction model based on representation learning and graph convolutional networks by Tun Li, Yanbing Liu, Qilie Liu, Wei Xu, Yunpeng Xiao, Hong Liu

“…The complexity of network structure, diversity of network nodes, and sparsity of data all pose difficulties in predicting propagation. …”
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Nearly-optimal bounds for sparse recovery in generic norms, with applications to k-median sketching by Woodruff, David P., Backurs, Arturs, Indyk, Piotr, Razenshteyn, Ilya

“…We initiate the study of trade-offs between sparsity and the number of measurements in sparse recovery schemes for generic norms. …”
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Deterministic Coresets for Stochastic Matrices with Applications to Scalable Sparse PageRank by Lang, Harry, Baykal, Cenk, Samra, Najib Abu, Tannous, Tony, Feldman, Dan, Rus, Daniela

“…Our algorithm takes advantage of this sparsity, assuming the out-degree of each node at most s, and terminates in O(ns/ε 2 ) time. …”
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Evolutionary constraints on visual cortex architecture from the dynamics of hallucinations by Butler, Thomas Charles, Benayoun, Marc, Wallace, Edward, van Drongelen, Wim, Goldenfeld, Nigel, Cowan, Jack

“…Our results provide an explanation for the observed sparsity of long-range inhibition in V1—this generic architectural feature is an evolutionary adaptation that tunes V1 to the normal vision state. …”
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Focused active inference by Levine, Daniel S., Ph. D. Massachusetts Institute of Technology

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Structure-aware multimodal feature fusion for RGB-D scene classification and beyond by Wang, Anran, Cai, Jianfei, Lu, Jiwen, Cham, Tat-Jen

“…In particular, for action recognition, we enforce interpart sparsity to choose more discriminative body parts, and intermodal nonsparsity to make informative features from both appearance and motion modalities coexist. …”
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Multimode process monitoring based on robust dictionary learning with application to aluminium electrolysis process by Yang, Chunhua, Zhou, Longfei, Huang, Keke, Ji, Hongquan, Long, Cheng, Chen, Xiaofang, Xie, Yongfang

“…Firstly, by taking the sparsity of outliers into account, a robust dictionary learning method is proposed to identify and remove the outliers and noise in the sampled training data. …”
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Review-based collaborative recommender system using deep learning methods by Da’u, Aminu

“…One major drawback of these approaches is the data sparsity problem, which generally leads to low performances of the recommender systems. …”
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Hermite interpolant multiscaling functions for numerical solution of the convection diffusion equations by Elmira Ashpazzadeh, Mehrdad Lakestani

“…The operational matrices of derivative, integration and product are presented for multiscaling functions and are utilized to reduce the solution of linear Convection-diusion equation to the solution of algebraic equations. Because of sparsity of these matrices, this method is computationally very attractive and reduces the CPU time and computer memory. …”
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Combined Sparsifying Transforms for Compressive Image Fusion by ZHAO, L., XU, X., WANG, H., WU, C.

“…Then, combined sparsifying transforms are presented to enhance the sparsity of images. Finally, a reconstruction algorithm based on the nonlinear conjugate gradient is presented to get the fused image. …”
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OldSlavNet: A scalable Early Slavic dependency parser trained on modern language data by Pedrazzini, N, Eckhoff, HM

“…Syntactically annotated texts are often a sine-qua-non in their modelling, but parsing of pre-modern language varieties faces great data sparsity, intensified by high levels of orthographic variation. …”