Jian Fang

Orcid: 0000-0001-5524-764X

Affiliations:
  • Tulane University, Biomedical Engineering Department, New Orleans, LA, USA
  • Xi'an Jiaotong University, School of Mathematics and Statistics, Xi'an, ShaanXi, China


According to our database1, Jian Fang authored at least 24 papers between 2012 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2022
Learning With Selected Features.
IEEE Trans. Cybern., 2022

2021
A Latent Gaussian Copula Model for Mixed Data Analysis in Brain Imaging Genetics.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

2020
Learning Through Deterministic Assignment of Hidden Parameters.
IEEE Trans. Cybern., 2020

Integration of Imaging (epi)Genomics Data for the Study of Schizophrenia Using Group Sparse Joint Nonnegative Matrix Factorization.
IEEE ACM Trans. Comput. Biol. Bioinform., 2020

2019
Aberrant Brain Connectivity in Schizophrenia Detected via a Fast Gaussian Graphical Model.
IEEE J. Biomed. Health Informatics, 2019

2018
Fast and Accurate Detection of Complex Imaging Genetics Associations Based on Greedy Projected Distance Correlation.
IEEE Trans. Medical Imaging, 2018

Joint Detection of Associations Between DNA Methylation and Gene Expression From Multiple Cancers.
IEEE J. Biomed. Health Informatics, 2018

EPS-LASSO: test for high-dimensional regression under extreme phenotype sampling of continuous traits.
Bioinform., 2018

High dimensional latent Gaussian copula model for mixed data in imaging genetics.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Detection of differentially developed functional connectivity patterns in adolescents based on tensor discriminative analysis.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Integration of multiple genomic imaging data for the study of schizophrenia using joint nonnegative matrix factorization.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Learning and approximation capabilities of orthogonal super greedy algorithm.
Knowl. Based Syst., 2016

The general critical analysis for continuous-time UPPAM recurrent neural networks.
Neurocomputing, 2016

Joint sparse canonical correlation analysis for detecting differential imaging genetics modules.
Bioinform., 2016

2015
Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part I).
IEEE Trans. Neural Networks Learn. Syst., 2015

Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part II).
IEEE Trans. Neural Networks Learn. Syst., 2015

2014
Fast Compressed Sensing SAR Imaging Based on Approximated Observation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014

Learning Rates of <i>l<sup>q</sup></i> Coefficient Regularization Learning with Gaussian Kernel.
Neural Comput., 2014

Learning and approximation capability of orthogonal super greedy algorithm.
CoRR, 2014

2013
Learning rates of l<sup>q</sup> coefficient regularization learning with Gaussian kernel.
CoRR, 2013

Compressed Sensing SAR Imaging with Multilook Processing.
CoRR, 2013

2012
Sparse SAR imaging based on L 1/2 regularization.
Sci. China Inf. Sci., 2012

Efficient DPCA SAR imaging with fast iterative spectrum reconstruction method.
Sci. China Inf. Sci., 2012

SAR range ambiguity suppression via sparse regularization.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012


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