Enhancing genomic mutation data storage optimization based on the compression of asymmetry of sparsity by Youde Ding, Youde Ding, Yuan Liao, Ji He, Jianfeng Ma, Xu Wei, Xuemei Liu, Guiying Zhang, Guiying Zhang, Jing Wang, Jing Wang

“…COO decompression performance was the worst. With increasing sparsity, the COO, CSC and CA_SAGM algorithms all exhibited longer compression and decompression times, lower compression and decompression rates, larger compression memory and lower compression ratios. …”
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Multiple Sound Sources Localization with Frame-by-Frame Component Removal of Statistically Dominant Source by Maoshen Jia, Yuxuan Wu, Changchun Bao, Jing Wang

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An efficient one-step proximal method for EIT sparse reconstruction based on nonstationary iterated Tikhonov regularization by Jing Wang

“…The proposed one-step PNITR method consists of twofold: one first performs NITR with mth iteration to generate the reference approximation, and then performs one-step proximal shrinkage processing and one forcing constraint function on it to obtain the final sparsity-promoting reconstruction. For the latter, the former aims to not only enhance higher reliability but also guarantee the sparsity. …”
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A multi-attention deep neural network model base on embedding and matrix factorization for recommendation by Jing Wang, Lei Liu

“…By integrating user / item embedding representation and matrix factorization representation, data sparsity and cold start problems can be effectively alleviated. …”
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A Compressed Data Partition and Loop Scheduling Scheme for Neural Networks by Dejian Li, Rongqiang Fang, Jing Wang, Dongyan Zhao, Ting Chong, Zengmin Ren, Jun Ma

“…We establish the compression efficiency model of the matrix sparse algorithm and design a partition selection method based on sparsity characteristics analyzed by the compression efficiency model. …”
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Predicting local persistence/recurrence after radiation therapy for head and neck cancer from PET/CT using a multi-objective, multi-classifier radiomics model by Qiongwen Zhang, Kai Wang, Zhiguo Zhou, Genggeng Qin, Lei Wang, Ping Li, David Sher, Steve Jiang, Jing Wang

“…For each imaging modality, we extracted 257 radiomic features to build a multi-objective radiomics model with sensitivity, specificity, and feature sparsity as objectives for model training. Multiple representative classifiers were combined to construct the predictive model. …”
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