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Jing Qin 0003
Person information
- affiliation: University of Kentucky, Department of Mathematics, Lexington, KY, USA
- affiliation (former): Montana State University, Department of Mathematical Sciences, Bozeman, MT, USA
- affiliation (2013 - 2016): University of California Los Angeles, Department of Mathematics, CA, USA
- affiliation (PhD 2013): Case Western Reserve University, Department of Mathematics, Cleveland, OH, USA
Other persons with the same name
- Jing Qin — disambiguation page
- Harry Qin (aka: Jing Qin 0001) — Hong Kong Polytechnic University, School of Nursing, Centre for Smart Health, Hong Kong (and 3 more)
- Jing Qin 0002 — Shandong University, School of Mathematics, Jinan, China
- Jing Qin 0004 — Chinese University of Hong Kong, School of Life Sciences, Hong Kong (and 1 more)
- Jing Qin 0005 — Northeastern University, School of Computer Science and Engineering, Shenyang, China
- Jing Qin 0006 — University of Southern Denmark, Department of Mathematics and Computer Science, Odense, Denmark (and 2 more)
- Jing Qin 0007 — Dalian University, School of Software Engineering, Dalian, China
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Journal Articles
- 2024
- [j10]Halyun Jeong, Deanna Needell, Jing Qin:
Federated Gradient Matching Pursuit. IEEE Trans. Inf. Theory 70(6): 4512-4537 (2024) - 2021
- [j9]Weihong Guo, Yifei Lou, Jing Qin, Ming Yan:
A Novel Regularization Based on the Error Function for Sparse Recovery. J. Sci. Comput. 87(1): 31 (2021) - [j8]Xuemei Chen, Jing Qin:
Regularized Kaczmarz Algorithms for Tensor Recovery. SIAM J. Imaging Sci. 14(4): 1439-1471 (2021) - [j7]Jing Qin, Harlin Lee, Jocelyn T. Chi, Lucas Drumetz, Jocelyn Chanussot, Yifei Lou, Andrea L. Bertozzi:
Blind Hyperspectral Unmixing Based on Graph Total Variation Regularization. IEEE Trans. Geosci. Remote. Sens. 59(4): 3338-3351 (2021) - 2020
- [j6]Yuying Shi, Zhimei Huo, Jing Qin, Yilin Li:
Automatic prior shape selection for image edge detection with modified Mumford-Shah model. Comput. Math. Appl. 79(6): 1644-1660 (2020) - [j5]Mujibur Rahman Chowdhury, Jing Qin, Yifei Lou:
Non-blind and Blind Deconvolution Under Poisson Noise Using Fractional-Order Total Variation. J. Math. Imaging Vis. 62(9): 1238-1255 (2020) - 2017
- [j4]Fang Li, Jing Qin:
Robust fuzzy local information and L p -norm distance-based image segmentation method. IET Image Process. 11(4): 217-226 (2017) - 2016
- [j3]Fang Li, Stanley J. Osher, Jing Qin, Ming Yan:
A Multiphase Image Segmentation Based on Fuzzy Membership Functions and L1-Norm Fidelity. J. Sci. Comput. 69(1): 82-106 (2016) - 2014
- [j2]Jing Xu, Huibin Chang, Jing Qin:
Domain decomposition method for image deblurring. J. Comput. Appl. Math. 271: 401-414 (2014) - [j1]Weihong Guo, Jing Qin, Wotao Yin:
A New Detail-Preserving Regularization Scheme. SIAM J. Imaging Sci. 7(2): 1309-1334 (2014)
Conference and Workshop Papers
- 2023
- [c17]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Natural Thresholding Algorithms. ACSSC 2023: 832-836 - 2021
- [c16]Igor Yanovsky, Jing Qin:
Spatio-Temporal Super-Resolution Reconstruction of Remote Sensing Data. IGARSS 2021: 2907-2910 - 2020
- [c15]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery. ITA 2020: 1-5 - 2019
- [c14]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Jointly Sparse Signal Recovery with Prior Info. ACSSC 2019: 645-649 - [c13]Jing Qin, Yifei Lou:
L1-2 Regularized Logistic Regression. ACSSC 2019: 779-783 - [c12]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Fast Hyperspectral Diffuse Optical Imaging Method with Joint Sparsity. EMBC 2019: 4758-4761 - [c11]Jing Qin, Harlin Lee, Jocelyn T. Chi, Yifei Lou, Jocelyn Chanussot, Andrea L. Bertozzi:
Fast Blind Hyperspectral Unmixing Based On Graph Laplacian. WHISPERS 2019: 1-5 - 2018
- [c10]Jing Qin, Yushan Wang, Wentai Liu:
Current Design with Minimum Error in Transcranial Direct Current Stimulation. BI 2018: 52-62 - [c9]Feng Liu, Shouyi Wang, Jing Qin, Yifei Lou, Jay M. Rosenberger:
Estimating Latent Brain Sources with Low-Rank Representation and Graph Regularization. BI 2018: 304-316 - [c8]Jing Qin, Igor Yanovsky:
Robust Super-Resolution Image Reconstruction Method for Geometrically Deformed Remote Sensing Images. IGARSS 2018: 8050-8053 - [c7]Jing Qin, Xiyu Yi, Shimon Weiss:
A novel fluorescence microscopy image deconvolution approach. ISBI 2018: 441-444 - 2017
- [c6]Feng Liu, Jing Qin, Shouyi Wang, Jay M. Rosenberger, Jianzhong Su:
Supervised EEG Source Imaging with Graph Regularization in Transformed Domain. BI 2017: 59-71 - [c5]Jing Qin, Feng Liu, Shouyi Wang, Jay M. Rosenberger:
EEG source imaging based on spatial and temporal graph structures. IPTA 2017: 1-6 - [c4]Jing Qin, Tianyu Wu, Ying Li, Wotao Yin, Stanley J. Osher, Wentai Liu:
Accelerated high-resolution EEG source imaging. NER 2017: 1-4 - 2016
- [c3]Ying Li, Jing Qin, Stanley J. Osher, Wentai Liu:
Graph fractional-order total variation EEG source reconstruction. EMBC 2016: 101-104 - 2013
- [c2]Jing Qin, Weihong Guo:
An efficient compressive sensing MR image reconstruction scheme. ISBI 2013: 306-309 - 2011
- [c1]Jing Qin, Weihong Guo:
An automatic additive and multiplicative noise removal scheme with sharpness preservation. ISBI 2011: 1819-1822
Informal and Other Publications
- 2024
- [i12]Weihong Guo, Yifei Lou, Jing Qin, Ming Yan:
Time-Varying Graph Signal Recovery Using High-Order Smoothness and Adaptive Low-rankness. CoRR abs/2405.09752 (2024) - 2023
- [i11]Halyun Jeong, Deanna Needell, Jing Qin:
Federated Gradient Matching Pursuit. CoRR abs/2302.10755 (2023) - [i10]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Natural Thresholding Algorithms. CoRR abs/2306.04730 (2023) - 2021
- [i9]Xuemei Chen, Jing Qin:
Regularized Kaczmarz Algorithms for Tensor Recovery. CoRR abs/2102.06852 (2021) - 2020
- [i8]Weihong Guo, Yifei Lou, Jing Qin, Ming Yan:
A Novel Regularization Based on the Error Function for Sparse Recovery. CoRR abs/2007.02784 (2020) - 2019
- [i7]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Iterative Hard Thresholding for Low CP-rank Tensor Models. CoRR abs/1908.08479 (2019) - [i6]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery. CoRR abs/1909.10132 (2019) - 2018
- [i5]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Compressed Anomaly Detection with Multiple Mixed Observations. CoRR abs/1801.10264 (2018) - 2017
- [i4]Jing Qin, Shuang Li, Deanna Needell, Anna Ma, Rachel Grotheer, Chenxi Huang, Natalie Durgin:
Stochastic Greedy Algorithms For Multiple Measurement Vectors. CoRR abs/1711.01521 (2017) - [i3]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors. CoRR abs/1711.02743 (2017) - 2015
- [i2]Fang Li, Stanley J. Osher, Jing Qin, Ming Yan:
A Multiphase Image Segmentation Based on Fuzzy Membership Functions and L1-norm Fidelity. CoRR abs/1504.02206 (2015) - 2014
- [i1]Jing Qin, Weihong Guo:
Two-stage Geometric Information Guided Image Reconstruction. CoRR abs/1409.7450 (2014)
Coauthor Index
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