Progressive Principal Component Analysis. - Jun Liu 003; Songcan Chen; Zhi-Hua Zhou (ISNN (1), 2004)

Making FLDA applicable to face recognition with one sample per person. - Songcan Chen; Jun Liu 003; Zhi-Hua Zhou (Pattern Recognit., 2004)

Resampling LDA/QR and PCA+LDA for Face Recognition. - Jun Liu 003; Songcan Chen (Australian Conference on Artificial Intelligence, 2005)

Weighted SOM-Face: Selecting Local Features for Recognition from Individual Face Image. - Xiaoyang Tan; Jun Liu 003; Songcan Chen; Fuyan Zhang (IDEAL, 2005)

Representing Image Matrices: Eigenimages Versus Eigenvectors. - Daoqiang Zhang; Songcan Chen; Jun Liu 003 (ISNN (2), 2005)

Recognition from a Single Sample per Person with Multiple SOM Fusion. - Xiaoyang Tan; Jun Liu 003; Songcan Chen (ISNN (2), 2006)

Sub-intrapersonal space analysis for face recognition. - Xiaoyang Tan; Jun Liu 003; Songcan Chen (Neurocomputing, 2006)

Discriminant common vectors versus neighbourhood components analysis and Laplacianfaces: A comparative study in small sample size problem. - Jun Liu 003; Songcan Chen (Image Vis. Comput., 2006)

Non-iterative generalized low rank approximation of matrices. - Jun Liu 003; Songcan Chen (Pattern Recognit. Lett., 2006)

Single Image Subspace for Face Recognition. - Jun Liu 003; Songcan Chen; Zhi-Hua Zhou; Xiaoyang Tan (AMFG, 2007)

Efficient Pseudoinverse Linear Discriminant Analysis and its Nonlinear Form for Face Recognition. - Jun Liu 003; Songcan Chen; Xiaoyang Tan; Daoqiang Zhang (Int. J. Pattern Recognit. Artif. Intell., 2007)

Comments on "Efficient and Robust Feature Extraction by Maximum Margin Criterion". - Jun Liu 003; Songcan Chen; Xiaoyang Tan; Daoqiang Zhang (IEEE Trans. Neural Networks, 2007)

A study on three linear discriminant analysis based methods in small sample size problem. - Jun Liu 003; Songcan Chen; Xiaoyang Tan (Pattern Recognit., 2008)

Fractional order singular value decomposition representation for face recognition. - Jun Liu 003; Songcan Chen; Xiaoyang Tan (Pattern Recognit., 2008)

Pattern Representation in Feature Extraction and Classifier Design: Matrix Versus Vector. - Zhe Wang 002; Songcan Chen; Jun Liu 003; Daoqiang Zhang (IEEE Trans. Neural Networks, 2008)

Robust faces manifold modeling: Most expressive Vs. most Sparse criterion. - Xiaoyang Tan; Lishan Qiao; Wenjuan Gao; Jun Liu 003 (ICCV Workshops, 2009)

A convex formulation for learning shared structures from multiple tasks. - Jianhui Chen; Lei Tang 001; Jun Liu 003; Jieping Ye (ICML, 2009)

Efficient Euclidean projections in linear time. - Jun Liu 003; Jieping Ye (ICML, 2009)

Learning the Optimal Neighborhood Kernel for Classification. - Jun Liu 003; Jianhui Chen; Songcan Chen; Jieping Ye (IJCAI, 2009)

Large-scale sparse logistic regression. - Jun Liu 003; Jianhui Chen; Jieping Ye (KDD, 2009)

Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation. - Liang Sun 001; Rinkal Patel; Jun Liu 003; Kewei Chen 001; Teresa Wu; Jing Li 016; Eric Reiman; Jieping Ye (KDD, 2009)

Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data. - Shuai Huang 001; Jing Li 016; Liang Sun 001; Jun Liu 003; Teresa Wu; Kewei Chen 001; Adam Fleisher; Eric Reiman; Jieping Ye (NIPS, 2009)

Efficient Recovery of Jointly Sparse Vectors. - Liang Sun 001; Jun Liu 003; Jianhui Chen; Jieping Ye (NIPS, 2009)

Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization. - Jun Liu 003; Shuiwang Ji; Jieping Ye (UAI, 2009)

Semi-random subspace method for face recognition. - Yulian Zhu; Jun Liu 003; Songcan Chen (Image Vis. Comput., 2009)

Face recognition under occlusions and variant expressions with partial similarity. - Xiaoyang Tan; Songcan Chen; Zhi-Hua Zhou; Jun Liu 003 (IEEE Trans. Inf. Forensics Secur., 2009)

Face Liveness Detection from a Single Image with Sparse Low Rank Bilinear Discriminative Model. - Xiaoyang Tan; Yi Li; Jun Liu 003; Lin Jiang (ECCV (6), 2010)

An efficient algorithm for a class of fused lasso problems. - Jun Liu 003; Lei Yuan 001; Jieping Ye (KDD, 2010)

Moreau-Yosida Regularization for Grouped Tree Structure Learning. - Jun Liu 003; Jieping Ye (NIPS, 2010)

Fast Overlapping Group Lasso - Jun Liu 003; Jieping Ye (CoRR, 2010)

Efficient L1/Lq Norm Regularization - Jun Liu 003; Jieping Ye (CoRR, 2010)

The Group Dantzig Selector. - Han Liu 001; Jian Zhang 003; Xiaoye Jiang; Jun Liu 003 (AISTATS, 2010)

Generalized low-rank approximations of matrices revisited. - Jun Liu 003; Songcan Chen; Zhi-Hua Zhou; Xiaoyang Tan (IEEE Trans. Neural Networks, 2010)

A multi-task learning formulation for predicting disease progression. - Jiayu Zhou; Lei Yuan 001; Jun Liu 003; Jieping Ye (KDD, 2011)

Projection onto A Nonnegative Max-Heap. - Jun Liu 003; Liang Sun 001; Jieping Ye (NIPS, 2011)

The Image Matting Method with Regularized Matte. - Junbin Gao; Manoranjan Paul; Jun Liu 003 (ICME, 2012)

Improved Nystrom Low-rank Decomposition with Priors. - Kai Zhang 001; Liang Lan; Jun Liu 003; Andreas Rauber (ICML, 2012)

Accelerated singular value thresholding for matrix completion. - Yao Hu; Debing Zhang; Jun Liu 003; Jieping Ye; Xiaofei He 001 (KDD, 2012)

A sparsity-inducing formulation for evolutionary co-clustering. - Shuiwang Ji; Wenlu Zhang; Jun Liu 003 (KDD, 2012)

Modeling disease progression via fused sparse group lasso. - Jiayu Zhou; Jun Liu 003; Vaibhav A. Narayan; Jieping Ye (KDD, 2012)

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis. - Daoqiang Zhang; Jun Liu 003; Dinggang Shen (MICCAI (3), 2012)

Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization - Jun Liu 003; Shuiwang Ji; Jieping Ye (CoRR, 2012)

Inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method - Kai Zhang 001; Liang Lan; Jun Liu 003; Andreas Rauber; Fabian Moerchen (CoRR, 2012)

Sparse non-negative tensor factorization using columnwise coordinate descent. - Ji Liu 002; Jun Liu 003; Peter Wonka; Jieping Ye (Pattern Recognit., 2012)

Sparse methods for biomedical data. - Jieping Ye; Jun Liu 003 (SIGKDD Explor., 2012)

Tight frame learning for cardiovascular MRI. - Qiu Wang; Jun Liu 003; Nirmal Janardhanan; Michael O. Zenge; Edgar Mueller; Mariappan S. Nadar (ISBI, 2013)

Safe Screening With Variational Inequalities and Its Applicaiton to LASSO. - Jun Liu 003; Zheng Zhao; Jie Wang 005; Jieping Ye (CoRR, 2013)

Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods. - Jie Wang 005; Jun Liu 003; Jieping Ye (CoRR, 2013)

Safe and Efficient Screening For Sparse Support Vector Machine. - Zheng Zhao; Jun Liu 003 (CoRR, 2013)

Modeling disease progression via multi-task learning. - Jiayu Zhou; Jun Liu 003; Vaibhav A. Narayan; Jieping Ye (NeuroImage, 2013)

A Convex Formulation for Learning a Shared Predictive Structure from Multiple Tasks. - Jianhui Chen; Lei Tang 001; Jun Liu 003; Jieping Ye (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Efficient Methods for Overlapping Group Lasso. - Lei Yuan 001; Jun Liu 003; Jieping Ye (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

An Adaptive Approach to Learning Optimal Neighborhood Kernels. - Xinwang Liu 002; Jianping Yin; Lei Wang 001; Lingqiao Liu; Jun Liu 003; Chenping Hou; Jian Zhang 002 (IEEE Trans. Cybern., 2013)

Safe Screening with Variational Inequalities and Its Application to Lasso. - Jun Liu 003; Zheng Zhao; Jie Wang 005; Jieping Ye (ICML, 2014)

Safe and efficient screening for sparse support vector machine. - Zheng Zhao; Jun Liu 003; James Cox (KDD, 2014)

A Safe Screening Rule for Sparse Logistic Regression. - Jie Wang 005; Jiayu Zhou; Jun Liu 003; Peter Wonka; Jieping Ye (NIPS, 2014)

Accelerating Model Selection with Safe Screening for L 1-Regularized L 2-SVM. - Zheng Zhao; Jun Liu 003; James Cox (ECML/PKDD (3), 2014)

Successive Ray Refinement and Its Application to Coordinate Descent for LASSO. - Jun Liu 003; Zheng Zhao; Ruiwen Zhang (CoRR, 2015)

Successive Ray Refinement and Its Application to Coordinate Descent for Lasso. - Jun Liu 003; Zheng Zhao; Ruiwen Zhang; Yan Xu (IDEAL, 2016)

Absolute Fused Lasso and Its Application to Genome-Wide Association Studies. - Tao Yang 016; Jun Liu 003; Pinghua Gong; Ruiwen Zhang; Xiaotong Shen; Jieping Ye (KDD, 2016)

Low-rank decomposition meets kernel learning: A generalized Nyström method. - Liang Lan; Kai Zhang 001; Hancheng Ge; Wei Cheng 002; Jun Liu 003; Andreas Rauber; Xiaoli Li 001; Jun Wang 006; Hongyuan Zha (Artif. Intell., 2017)

Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease. - Biao Jie; Mingxia Liu 001; Jun Liu 003; Daoqiang Zhang; Dinggang Shen (IEEE Trans. Biomed. Eng., 2017)

D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. - Taoxing Pan; Jun Liu 003; Jie Wang 005 (AAAI, 2020)

The Fifth International Workshop on Automation in Machine Learning. - Tao Wang; Patrick Koch; Brett Wujek; Jun Liu 003; Hai Li 001 (KDD, 2021)

3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve. - Lei Wang 108; Jun Liu 003; Piotr Koniusz (CoRR, 2021)

The Sixth International Workshop on Automation in Machine Learning. - Patrick Koch; Brett Wujek; Jun Liu 003; Jun Huan; Tao Wang (KDD, 2022)

IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding. - Lanyun Zhu; Deyi Ji; Tianrun Chen; Peng Xu; Jieping Ye; Jun Liu 003 (CoRR, 2024)