Jun Liu - RankMe

69 papers A* 17A 3C 2Journal 31Unranked 16

Year	Rank	Type	Title / Venue / Authors
2022	A*	`conf`	The Sixth International Workshop on Automation in Machine Learning. KDD Patrick Koch, Brett Wujek, Jun Liu, Jun Huan, Tao Wang
2021	J	`jnl`	3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve. CoRR Lei Wang, Jun Liu, Piotr Koniusz
2021	A*	`conf`	The Fifth International Workshop on Automation in Machine Learning. KDD Tao Wang, Patrick Koch, Brett Wujek, Jun Liu, Hai Li
2020	A*	`conf`	D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. AAAI Taoxing Pan, Jun Liu, Jie Wang
2019	J	`jnl`	D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. CoRR Taoxing Pan, Jun Liu, Jie Wang
2017	J	`jnl`	Low-rank decomposition meets kernel learning: A generalized Nyström method. Artif. Intell. Liang Lan, Kai Zhang, Hancheng Ge, Wei Cheng, Jun Liu, Andreas Rauber, Xiaoli Li, Jun Wang, Hongyuan Zha
2017	J	`jnl`	Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease. IEEE Trans. Biomed. Eng. Biao Jie, Mingxia Liu, Jun Liu, Daoqiang Zhang, Dinggang Shen
2016	A*	`conf`	Absolute Fused Lasso and Its Application to Genome-Wide Association Studies. KDD Tao Yang, Jun Liu, Pinghua Gong, Ruiwen Zhang, Xiaotong Shen, Jieping Ye
2016	C	`conf`	Successive Ray Refinement and Its Application to Coordinate Descent for Lasso. IDEAL Jun Liu, Zheng Zhao, Ruiwen Zhang, Yan Xu
2015	J	`jnl`	Successive Ray Refinement and Its Application to Coordinate Descent for LASSO. CoRR Jun Liu, Zheng Zhao, Ruiwen Zhang
2014	—	`conf`	A Safe Screening Rule for Sparse Logistic Regression. NIPS Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye
2014	—	`conf`	Accelerating Model Selection with Safe Screening for L 1-Regularized L 2-SVM. ECML/PKDD (3) Zheng Zhao, Jun Liu, James Cox
2014	A*	`conf`	Safe Screening with Variational Inequalities and Its Application to Lasso. ICML Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye
2014	A*	`conf`	Safe and efficient screening for sparse support vector machine. KDD Zheng Zhao, Jun Liu, James Cox
2013	J	`jnl`	A Convex Formulation for Learning a Shared Predictive Structure from Multiple Tasks. IEEE Trans. Pattern Anal. Mach. Intell. Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye
2013	J	`jnl`	A Safe Screening Rule for Sparse Logistic Regression. CoRR Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye
2013	J	`jnl`	An Adaptive Approach to Learning Optimal Neighborhood Kernels. IEEE Trans. Cybern. Xinwang Liu, Jianping Yin, Lei Wang, Lingqiao Liu, Jun Liu, Chenping Hou, Jian Zhang
2013	J	`jnl`	Efficient Methods for Overlapping Group Lasso. IEEE Trans. Pattern Anal. Mach. Intell. Lei Yuan, Jun Liu, Jieping Ye
2013	J	`jnl`	Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods. CoRR Jie Wang, Jun Liu, Jieping Ye
2013	J	`jnl`	Modeling disease progression via multi-task learning. NeuroImage Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye
2013	J	`jnl`	Safe Screening With Variational Inequalities and Its Applicaiton to LASSO. CoRR Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye
2013	J	`jnl`	Safe and Efficient Screening For Sparse Support Vector Machine. CoRR Zheng Zhao, Jun Liu
2013	—	`conf`	Tight frame learning for cardiovascular MRI. ISBI Qiu Wang, Jun Liu, Nirmal Janardhanan, Michael O. Zenge, Edgar Mueller, Mariappan S. Nadar
2012	A*	`conf`	A sparsity-inducing formulation for evolutionary co-clustering. KDD Shuiwang Ji, Wenlu Zhang, Jun Liu
2012	A*	`conf`	Accelerated singular value thresholding for matrix completion. KDD Yao Hu, Debing Zhang, Jun Liu, Jieping Ye, Xiaofei He
2012	A*	`conf`	Improved Nystrom Low-rank Decomposition with Priors. ICML Kai Zhang, Liang Lan, Jun Liu, Andreas Rauber
2012	J	`jnl`	Inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method CoRR Kai Zhang, Liang Lan, Jun Liu, Andreas Rauber, Fabian Moerchen
2012	A*	`conf`	Modeling disease progression via fused sparse group lasso. KDD Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye
2012	J	`jnl`	Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization CoRR Jun Liu, Shuiwang Ji, Jieping Ye
2012	J	`jnl`	Sparse methods for biomedical data. SIGKDD Explor. Jieping Ye, Jun Liu
2012	J	`jnl`	Sparse non-negative tensor factorization using columnwise coordinate descent. Pattern Recognit. Ji Liu, Jun Liu, Peter Wonka, Jieping Ye
2012	—	`conf`	Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis. MICCAI (3) Daoqiang Zhang, Jun Liu, Dinggang Shen
2012	A	`conf`	The Image Matting Method with Regularized Matte. ICME Junbin Gao, Manoranjan Paul, Jun Liu
2011	A*	`conf`	A multi-task learning formulation for predicting disease progression. KDD Jiayu Zhou, Lei Yuan, Jun Liu, Jieping Ye
2011	—	`conf`	Efficient Methods for Overlapping Group Lasso. NIPS Lei Yuan, Jun Liu, Jieping Ye
2011	—	`conf`	Projection onto A Nonnegative Max-Heap. NIPS Jun Liu, Liang Sun, Jieping Ye
2010	A*	`conf`	An efficient algorithm for a class of fused lasso problems. KDD Jun Liu, Lei Yuan, Jieping Ye
2010	J	`jnl`	Efficient L1/Lq Norm Regularization CoRR Jun Liu, Jieping Ye
2010	—	`conf`	Face Liveness Detection from a Single Image with Sparse Low Rank Bilinear Discriminative Model. ECCV (6) Xiaoyang Tan, Yi Li, Jun Liu, Lin Jiang
2010	J	`jnl`	Fast Overlapping Group Lasso CoRR Jun Liu, Jieping Ye
2010	J	`jnl`	Generalized low-rank approximations of matrices revisited. IEEE Trans. Neural Networks Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan
2010	—	`conf`	Moreau-Yosida Regularization for Grouped Tree Structure Learning. NIPS Jun Liu, Jieping Ye
2010	A	`conf`	The Group Dantzig Selector. AISTATS Han Liu, Jian Zhang, Xiaoye Jiang, Jun Liu
2009	A*	`conf`	A convex formulation for learning shared structures from multiple tasks. ICML Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye
2009	A*	`conf`	Efficient Euclidean projections in linear time. ICML Jun Liu, Jieping Ye
2009	—	`conf`	Efficient Recovery of Jointly Sparse Vectors. NIPS Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye
2009	J	`jnl`	Face recognition under occlusions and variant expressions with partial similarity. IEEE Trans. Inf. Forensics Secur. Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Jun Liu
2009	A*	`conf`	Large-scale sparse logistic regression. KDD Jun Liu, Jianhui Chen, Jieping Ye
2009	—	`conf`	Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data. NIPS Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye
2009	A*	`conf`	Learning the Optimal Neighborhood Kernel for Classification. IJCAI Jun Liu, Jianhui Chen, Songcan Chen, Jieping Ye
2009	A*	`conf`	Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation. KDD Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Teresa Wu, Jing Li, Eric Reiman, Jieping Ye
2009	A	`conf`	Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization. UAI Jun Liu, Shuiwang Ji, Jieping Ye
2009	—	`conf`	Robust faces manifold modeling: Most expressive Vs. most Sparse criterion. ICCV Workshops Xiaoyang Tan, Lishan Qiao, Wenjuan Gao, Jun Liu
2009	J	`jnl`	Semi-random subspace method for face recognition. Image Vis. Comput. Yulian Zhu, Jun Liu, Songcan Chen
2008	J	`jnl`	A study on three linear discriminant analysis based methods in small sample size problem. Pattern Recognit. Jun Liu, Songcan Chen, Xiaoyang Tan
2008	J	`jnl`	Fractional order singular value decomposition representation for face recognition. Pattern Recognit. Jun Liu, Songcan Chen, Xiaoyang Tan
2008	J	`jnl`	Pattern Representation in Feature Extraction and Classifier Design: Matrix Versus Vector. IEEE Trans. Neural Networks Zhe Wang, Songcan Chen, Jun Liu, Daoqiang Zhang
2007	J	`jnl`	Comments on "Efficient and Robust Feature Extraction by Maximum Margin Criterion". IEEE Trans. Neural Networks Jun Liu, Songcan Chen, Xiaoyang Tan, Daoqiang Zhang
2007	J	`jnl`	Efficient Pseudoinverse Linear Discriminant Analysis and its Nonlinear Form for Face Recognition. Int. J. Pattern Recognit. Artif. Intell. Jun Liu, Songcan Chen, Xiaoyang Tan, Daoqiang Zhang
2007	—	`conf`	Single Image Subspace for Face Recognition. AMFG Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan
2006	J	`jnl`	Discriminant common vectors versus neighbourhood components analysis and Laplacianfaces: A comparative study in small sample size problem. Image Vis. Comput. Jun Liu, Songcan Chen
2006	J	`jnl`	Non-iterative generalized low rank approximation of matrices. Pattern Recognit. Lett. Jun Liu, Songcan Chen
2006	—	`conf`	Recognition from a Single Sample per Person with Multiple SOM Fusion. ISNN (2) Xiaoyang Tan, Jun Liu, Songcan Chen
2006	J	`jnl`	Sub-intrapersonal space analysis for face recognition. Neurocomputing Xiaoyang Tan, Jun Liu, Songcan Chen
2005	—	`conf`	Representing Image Matrices: Eigenimages Versus Eigenvectors. ISNN (2) Daoqiang Zhang, Songcan Chen, Jun Liu
2005	—	`conf`	Resampling LDA/QR and PCA+LDA for Face Recognition. Australian Conference on Artificial Intelligence Jun Liu, Songcan Chen
2005	C	`conf`	Weighted SOM-Face: Selecting Local Features for Recognition from Individual Face Image. IDEAL Xiaoyang Tan, Jun Liu, Songcan Chen, Fuyan Zhang
2004	J	`jnl`	Making FLDA applicable to face recognition with one sample per person. Pattern Recognit. Songcan Chen, Jun Liu, Zhi-Hua Zhou
2004	—	`conf`	Progressive Principal Component Analysis. ISNN (1) Jun Liu, Songcan Chen, Zhi-Hua Zhou