Jun Liu

Publication Activity (10 Years)

Years Active: 2004-2020
Publications (10 Years): 6

Top Topics

Model Selection

Biomedical Data

Sparse Learning

Top Venues

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Taoxing Pan, Jun Liu, Jie Wang
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. AAAI (2020)
Taoxing Pan, Jun Liu, Jie Wang
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. CoRR (2019)
Liang Lan, Kai Zhang, Hancheng Ge, Wei Cheng, Jun Liu, Andreas Rauber, Xiaoli Li, Jun Wang, Hongyuan Zha
Low-rank decomposition meets kernel learning: A generalized Nyström method. Artif. Intell. 250 (2017)
Biao Jie, Mingxia Liu, Jun Liu, Daoqiang Zhang, Dinggang Shen
Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease. IEEE Trans. Biomed. Eng. 64 (1) (2017)
Jun Liu, Zheng Zhao, Ruiwen Zhang, Yan Xu
Successive Ray Refinement and Its Application to Coordinate Descent for Lasso. IDEAL (2016)
Tao Yang, Jun Liu, Pinghua Gong, Ruiwen Zhang, Xiaotong Shen, Jieping Ye
Absolute Fused Lasso and Its Application to Genome-Wide Association Studies. KDD (2016)
Jun Liu, Zheng Zhao, Ruiwen Zhang
Successive Ray Refinement and Its Application to Coordinate Descent for LASSO. CoRR (2015)
Zheng Zhao, Jun Liu, James Cox
Accelerating Model Selection with Safe Screening for L 1-Regularized L 2-SVM. ECML/PKDD (3) (2014)
Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye
Safe Screening with Variational Inequalities and Its Application to Lasso. ICML (2014)
Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye
A Safe Screening Rule for Sparse Logistic Regression. NIPS (2014)
Zheng Zhao, Jun Liu, James Cox
Safe and efficient screening for sparse support vector machine. KDD (2014)
Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye
A Safe Screening Rule for Sparse Logistic Regression. CoRR (2013)
Zheng Zhao, Jun Liu
Safe and Efficient Screening For Sparse Support Vector Machine. CoRR (2013)
Qiu Wang, Jun Liu, Nirmal Janardhanan, Michael O. Zenge, Edgar Mueller, Mariappan S. Nadar
Tight frame learning for cardiovascular MRI. ISBI (2013)
Jie Wang, Jun Liu, Jieping Ye
Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods. CoRR (2013)
Xinwang Liu, Jianping Yin, Lei Wang, Lingqiao Liu, Jun Liu, Chenping Hou, Jian Zhang
An Adaptive Approach to Learning Optimal Neighborhood Kernels. IEEE Trans. Cybern. 43 (1) (2013)
Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye
Safe Screening With Variational Inequalities and Its Applicaiton to LASSO. CoRR (2013)
Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye
Modeling disease progression via multi-task learning. NeuroImage 78 (2013)
Lei Yuan, Jun Liu, Jieping Ye
Efficient Methods for Overlapping Group Lasso. IEEE Trans. Pattern Anal. Mach. Intell. 35 (9) (2013)
Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye
A Convex Formulation for Learning a Shared Predictive Structure from Multiple Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 35 (5) (2013)
Kai Zhang, Liang Lan, Jun Liu, Andreas Rauber
Improved Nystrom Low-rank Decomposition with Priors. ICML (2012)
Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye
Modeling disease progression via fused sparse group lasso. KDD (2012)
Junbin Gao, Manoranjan Paul, Jun Liu
The Image Matting Method with Regularized Matte. ICME (2012)
Daoqiang Zhang, Jun Liu, Dinggang Shen
Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis. MICCAI (3) (2012)
Shuiwang Ji, Wenlu Zhang, Jun Liu
A sparsity-inducing formulation for evolutionary co-clustering. KDD (2012)
Ji Liu, Jun Liu, Peter Wonka, Jieping Ye
Sparse non-negative tensor factorization using columnwise coordinate descent. Pattern Recognit. 45 (1) (2012)
Jieping Ye, Jun Liu
Sparse methods for biomedical data. SIGKDD Explor. 14 (1) (2012)
Kai Zhang, Liang Lan, Jun Liu, Andreas Rauber, Fabian Moerchen
Inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method CoRR (2012)
Yao Hu, Debing Zhang, Jun Liu, Jieping Ye, Xiaofei He
Accelerated singular value thresholding for matrix completion. KDD (2012)
Jun Liu, Shuiwang Ji, Jieping Ye
Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization CoRR (2012)
Lei Yuan, Jun Liu, Jieping Ye
Efficient Methods for Overlapping Group Lasso. NIPS (2011)
Jiayu Zhou, Lei Yuan, Jun Liu, Jieping Ye
A multi-task learning formulation for predicting disease progression. KDD (2011)
Jun Liu, Liang Sun, Jieping Ye
Projection onto A Nonnegative Max-Heap. NIPS (2011)
Jun Liu, Jieping Ye
Moreau-Yosida Regularization for Grouped Tree Structure Learning. NIPS (2010)
Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan
Generalized low-rank approximations of matrices revisited. IEEE Trans. Neural Networks 21 (4) (2010)
Jun Liu, Jieping Ye
Efficient L1/Lq Norm Regularization CoRR (2010)
Jun Liu, Lei Yuan, Jieping Ye
An efficient algorithm for a class of fused lasso problems. KDD (2010)
Xiaoyang Tan, Yi Li, Jun Liu, Lin Jiang
Face Liveness Detection from a Single Image with Sparse Low Rank Bilinear Discriminative Model. ECCV (6) (2010)
Jun Liu, Jieping Ye
Fast Overlapping Group Lasso CoRR (2010)
Han Liu, Jian Zhang, Xiaoye Jiang, Jun Liu
The Group Dantzig Selector. AISTATS (2010)
Yulian Zhu, Jun Liu, Songcan Chen
Semi-random subspace method for face recognition. Image Vis. Comput. 27 (9) (2009)
Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye
A convex formulation for learning shared structures from multiple tasks. ICML (2009)
Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data. NIPS (2009)
Xiaoyang Tan, Lishan Qiao, Wenjuan Gao, Jun Liu
Robust faces manifold modeling: Most expressive Vs. most Sparse criterion. ICCV Workshops (2009)
Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Teresa Wu, Jing Li, Eric Reiman, Jieping Ye
Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation. KDD (2009)
Jun Liu, Jianhui Chen, Songcan Chen, Jieping Ye
Learning the Optimal Neighborhood Kernel for Classification. IJCAI (2009)
Jun Liu, Shuiwang Ji, Jieping Ye
Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization. UAI (2009)
Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Jun Liu
Face recognition under occlusions and variant expressions with partial similarity. IEEE Trans. Inf. Forensics Secur. 4 (2) (2009)
Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye
Efficient Recovery of Jointly Sparse Vectors. NIPS (2009)
Jun Liu, Jianhui Chen, Jieping Ye
Large-scale sparse logistic regression. KDD (2009)
Jun Liu, Jieping Ye
Efficient Euclidean projections in linear time. ICML (2009)
Jun Liu, Songcan Chen, Xiaoyang Tan
A study on three linear discriminant analysis based methods in small sample size problem. Pattern Recognit. 41 (1) (2008)
Zhe Wang, Songcan Chen, Jun Liu, Daoqiang Zhang
Pattern Representation in Feature Extraction and Classifier Design: Matrix Versus Vector. IEEE Trans. Neural Networks 19 (5) (2008)
Jun Liu, Songcan Chen, Xiaoyang Tan
Fractional order singular value decomposition representation for face recognition. Pattern Recognit. 41 (1) (2008)
Jun Liu, Songcan Chen, Xiaoyang Tan, Daoqiang Zhang
Efficient Pseudoinverse Linear Discriminant Analysis and its Nonlinear Form for Face Recognition. Int. J. Pattern Recognit. Artif. Intell. 21 (8) (2007)
Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan
Single Image Subspace for Face Recognition. AMFG (2007)
Jun Liu, Songcan Chen, Xiaoyang Tan, Daoqiang Zhang
Comments on "Efficient and Robust Feature Extraction by Maximum Margin Criterion". IEEE Trans. Neural Networks 18 (6) (2007)
Jun Liu, Songcan Chen
Discriminant common vectors versus neighbourhood components analysis and Laplacianfaces: A comparative study in small sample size problem. Image Vis. Comput. 24 (3) (2006)
Xiaoyang Tan, Jun Liu, Songcan Chen
Recognition from a Single Sample per Person with Multiple SOM Fusion. ISNN (2) (2006)
Xiaoyang Tan, Jun Liu, Songcan Chen
Sub-intrapersonal space analysis for face recognition. Neurocomputing 69 (13-15) (2006)
Jun Liu, Songcan Chen
Non-iterative generalized low rank approximation of matrices. Pattern Recognit. Lett. 27 (9) (2006)
Xiaoyang Tan, Jun Liu, Songcan Chen, Fuyan Zhang
Weighted SOM-Face: Selecting Local Features for Recognition from Individual Face Image. IDEAL (2005)
Daoqiang Zhang, Songcan Chen, Jun Liu
Representing Image Matrices: Eigenimages Versus Eigenvectors. ISNN (2) (2005)
Jun Liu, Songcan Chen
Resampling LDA/QR and PCA+LDA for Face Recognition. Australian Conference on Artificial Intelligence (2005)
Jun Liu, Songcan Chen, Zhi-Hua Zhou
Progressive Principal Component Analysis. ISNN (1) (2004)
Songcan Chen, Jun Liu, Zhi-Hua Zhou
Making FLDA applicable to face recognition with one sample per person. Pattern Recognit. 37 (7) (2004)