| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Yueran Qi, Yang Feng, Hai Wang, Chengcheng Wang, Maoying Bai, Jing Liu, Xuepeng Zhan, Jixuan Wu, Qianwen Wang, Jiezhi Che. Flash-Based Computing-in-Memory Architecture to Implement High-Precision Sparse Coding. Micromachines. vol 14. issue 12. 2023-12-23. PMID:38138359. |
here, a novel flash-based cim architecture is proposed to implement large-scale sparse coding, wherein various matrix weight training algorithms are verified. |
2023-12-23 |
2023-12-25 |
Not clear |
| Yusuke Endo, Koujin Taked. Performance Evaluation of Matrix Factorization for fMRI Data. Neural computation. 2023-12-05. PMID:38052077. |
in this study, we investigate the validity of sparse coding in the whole human brain by applying various matrix factorization methods to functional magnetic resonance imaging data of neural activities in the brain. |
2023-12-05 |
2023-12-10 |
human |
| Yusuke Endo, Koujin Taked. Performance Evaluation of Matrix Factorization for fMRI Data. Neural computation. 2023-12-05. PMID:38052077. |
the result suggests the sparse coding hypothesis in information representation in the whole human brain, because extracted features from the sparse matrix factorization (mf) method, sparse principal component analysis (sparsepca), or method of optimal directions (mod) under a high sparsity setting or an approximate sparse mf method, fast independent component analysis (fastica), can classify external visual stimuli more accurately than the nonsparse mf method or sparse mf method under a low sparsity setting. |
2023-12-05 |
2023-12-10 |
human |
| Xianglin Zuo, Tianhao Jia, Xin He, Bo Yang, Ying Wan. Exploiting Dual-Attention Networks for Explainable Recommendation in Heterogeneous Information Networks. Entropy (Basel, Switzerland). vol 24. issue 12. 2022-12-23. PMID:36554126. |
we first used multiple meta-paths to capture high-order semantic relations between users and items in hin for generating similarity matrices, and then utilized matrix decomposition on similarity matrices to obtain low-dimensional sparse representations of users and items. |
2022-12-23 |
2023-08-14 |
Not clear |
| Jie Chen, Shengxiang Yang, Xi Peng, Dezhong Peng, Zhu Wan. Augmented Sparse Representation for Incomplete Multiview Clustering. IEEE transactions on neural networks and learning systems. vol PP. 2022-09-07. PMID:36070269. |
then, we present a similarity fusion scheme, namely, a sparsity augmented fusion of sparse representations, to obtain a sparsity augmented similarity matrix across different views for spectral clustering. |
2022-09-07 |
2023-08-14 |
Not clear |
| Jiawei Wu, Hengyou Wan. Structural Smoothing Low-Rank Matrix Restoration Based on Sparse Coding and Dual-Weighted Model. Entropy (Basel, Switzerland). vol 24. issue 7. 2022-07-27. PMID:35885170. |
in this paper, we propose a low-rank matrix restoration model based on sparse coding and dual weighting. |
2022-07-27 |
2023-08-14 |
Not clear |
| Jiawei Wu, Hengyou Wan. Structural Smoothing Low-Rank Matrix Restoration Based on Sparse Coding and Dual-Weighted Model. Entropy (Basel, Switzerland). vol 24. issue 7. 2022-07-27. PMID:35885170. |
structural smoothing low-rank matrix restoration based on sparse coding and dual-weighted model. |
2022-07-27 |
2023-08-14 |
Not clear |
| Peng Peng, Yongfeng Ju, Yipu Zhang, Kaiming Wang, Suying Jiang, Yuping Wan. Sparse representation and dictionary learning model incorporating group sparsity and incoherence to extract abnormal brain regions associated with schizophrenia. IEEE access : practical innovations, open solutions. vol 8. 2021-09-29. PMID:33747675. |
the sdl method decomposed the fmri data into a sparse coding matrix |
2021-09-29 |
2023-08-13 |
Not clear |
| Esmeide Leal, German Sanchez-Torres, John W Branch-Bedoya, Francisco Abad, Nallig Lea. A Saliency-Based Sparse Representation Method for Point Cloud Simplification. Sensors (Basel, Switzerland). vol 21. issue 13. 2021-07-07. PMID:34201455. |
we perform the corresponding sparse coding process to produce a sparse matrix. |
2021-07-07 |
2023-08-13 |
Not clear |
| Carlos A Loz. RobOMP: Robust variants of Orthogonal Matching Pursuit for sparse representations. PeerJ. Computer science. vol 5. 2021-04-06. PMID:33816845. |
sparse coding aims to find a parsimonious representation of an example given an observation matrix or dictionary. |
2021-04-06 |
2023-08-13 |
Not clear |
| Xianhui Meng, Ming Liu, Peng Xiong, Jian Chen, Lin Yang, Xiuling Li. [Detection algorithm of paroxysmal atrial fibrillation with sparse coding based on Riemannian manifold]. Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi. vol 37. issue 4. 2020-08-26. PMID:32840086. |
sparse coding is applied to the manifold, and each covariance matrix is represented as a sparse linear combination of riemann dictionary atoms. |
2020-08-26 |
2023-08-13 |
Not clear |
| Ke Liu, Zhu Liang Yu, Wei Wu, Zhenghui Gu, Jun Zhang, Ling Cen, Srikantan Nagarajan, Yuanqing L. Bayesian Electromagnetic Spatio-Temporal Imaging of Extended Sources Based on Matrix Factorization. IEEE transactions on bio-medical engineering. vol 66. issue 9. 2020-04-27. PMID:30605088. |
the si-stbf is based on the factorization of a source matrix as a product of a sparse coding matrix and a temporal basis function (tbf) matrix, which includes a few tbfs. |
2020-04-27 |
2023-08-13 |
Not clear |
| Ao Li, Deyun Chen, Zhiqiang Wu, Guanglu Sun, Kezheng Li. Self-supervised sparse coding scheme for image classification based on low rank representation. PloS one. vol 13. issue 6. 2018-12-27. PMID:29924830. |
next, the low-rank representation matrix is used to characterize the similarity of samples in order to establish a self-supervised sparse coding model, which aims to preserve the local structure of codings for similar samples. |
2018-12-27 |
2023-08-13 |
Not clear |
| Liangli Zhen, Dezhong Peng, Zhang Yi, Yong Xiang, Peng Che. Underdetermined Blind Source Separation Using Sparse Coding. IEEE transactions on neural networks and learning systems. vol 28. issue 12. 2018-12-21. PMID:28113526. |
since the sparse coding strategy considers the linear representation relations among all the tf representation vectors of mixing signals, the proposed algorithm can provide an accurate estimation of the mixing matrix and is robust to the noises compared with the existing underdetermined blind source separation approaches. |
2018-12-21 |
2023-08-13 |
Not clear |
| Tongliang Liu, Dacheng Tao, Dong X. Dimensionality-Dependent Generalization Bounds for k-Dimensional Coding Schemes. Neural computation. vol 28. issue 10. 2018-08-28. PMID:27391679. |
the k-dimensional coding schemes refer to a collection of methods that attempt to represent data using a set of representative k-dimensional vectors and include nonnegative matrix factorization, dictionary learning, sparse coding, k-means clustering, and vector quantization as special cases. |
2018-08-28 |
2023-08-13 |
Not clear |
| Yudan Ren, Jun Fang, Jinglei Lv, Xintao Hu, Cong Christine Guo, Lei Guo, Jiansong Xu, Marc N Potenza, Tianming Li. Assessing the effects of cocaine dependence and pathological gambling using group-wise sparse representation of natural stimulus FMRI data. Brain imaging and behavior. vol 11. issue 4. 2018-08-27. PMID:27704410. |
specifically, natural stimulus fmri (n-fmri) signals from all three groups of subjects are aggregated into a big data matrix, which is then decomposed into a common signal basis dictionary and associated weight coefficient matrices via an effective online dictionary learning and sparse coding method. |
2018-08-27 |
2023-08-13 |
human |
| Yudan Ren, Jinglei Lv, Lei Guo, Jun Fang, Christine Cong Gu. Sparse coding reveals greater functional connectivity in female brains during naturalistic emotional experience. PloS one. vol 12. issue 12. 2018-01-16. PMID:29272294. |
an online dictionary learning and sparse coding algorithm was applied to the aggregated fmri signals from both groups, which was subsequently factorized into a common time series signal dictionary matrix and the associated weight coefficient matrix. |
2018-01-16 |
2023-08-13 |
Not clear |
| Jianwen Xie, Pamela K Douglas, Ying Nian Wu, Arthur L Brody, Ariana E Anderso. Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms. Journal of neuroscience methods. vol 282. 2017-11-16. PMID:28322859. |
decoding the encoding of functional brain networks: an fmri classification comparison of non-negative matrix factorization (nmf), independent component analysis (ica), and sparse coding algorithms. |
2017-11-16 |
2023-08-13 |
Not clear |
| Xi Yin, Ying-Ying Xu, Hong-Bin She. Enhancing the Prediction of Transmembrane β-Barrel Segments with Chain Learning and Feature Sparse Representation. IEEE/ACM transactions on computational biology and bioinformatics. vol 13. issue 6. 2017-10-02. PMID:26887010. |
we considered the relative status information between neighboring residues for enhancing the performance, and the matrix of features was translated into feature image by sparse coding algorithm for noise and dimension reduction. |
2017-10-02 |
2023-08-13 |
Not clear |
| Mehrtash T Harandi, Richard Hartley, Brian Lovell, Conrad Sanderso. Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences. IEEE transactions on neural networks and learning systems. vol 27. issue 6. 2017-05-24. PMID:25643414. |
we propose to seek sparse coding by embedding the space of spd matrices into the hilbert spaces through two types of the bregman matrix divergences. |
2017-05-24 |
2023-08-13 |
Not clear |