Jun Liu

According to our database, Jun Liu authored at least 67 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding.

Lanyun Zhu, Deyi Ji, Tianrun Chen, Peng Xu, Jieping Ye, Jun Liu

CoRR, 2024

2022

The Sixth International Workshop on Automation in Machine Learning.

Patrick Koch, Brett Wujek, Jun Liu, Jun Huan, Tao Wang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve.

Lei Wang, Jun Liu, Piotr Koniusz

CoRR, 2021

The Fifth International Workshop on Automation in Machine Learning.

Tao Wang, Patrick Koch, Brett Wujek, Jun Liu, Hai Li

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems.

Taoxing Pan, Jun Liu, Jie Wang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2017

Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease.

Biao Jie, Mingxia Liu, Jun Liu, Daoqiang Zhang, Dinggang Shen

IEEE Trans. Biomed. Eng., 2017

Low-rank decomposition meets kernel learning: A generalized Nyström method.

Liang Lan, Kai Zhang, Hancheng Ge, Wei Cheng, Jun Liu, Andreas Rauber, Xiaoli Li, Jun Wang, Hongyuan Zha

Artif. Intell., 2017

2016

Absolute Fused Lasso and Its Application to Genome-Wide Association Studies.

Tao Yang, Jun Liu, Pinghua Gong, Ruiwen Zhang, Xiaotong Shen, Jieping Ye

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Successive Ray Refinement and Its Application to Coordinate Descent for Lasso.

Jun Liu, Zheng Zhao, Ruiwen Zhang, Yan Xu

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2016, 2016

2015

Successive Ray Refinement and Its Application to Coordinate Descent for LASSO.

Jun Liu, Zheng Zhao, Ruiwen Zhang

CoRR, 2015

2014

Accelerating Model Selection with Safe Screening for L 1-Regularized L 2-SVM.

Zheng Zhao, Jun Liu, James Cox

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

A Safe Screening Rule for Sparse Logistic Regression.

Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Safe and efficient screening for sparse support vector machine.

Zheng Zhao, Jun Liu, James Cox

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Safe Screening with Variational Inequalities and Its Application to Lasso.

Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

An Adaptive Approach to Learning Optimal Neighborhood Kernels.

Xinwang Liu, Jianping Yin, Lei Wang, Lingqiao Liu, Jun Liu, Chenping Hou, Jian Zhang

IEEE Trans. Cybern., 2013

Efficient Methods for Overlapping Group Lasso.

Lei Yuan, Jun Liu, Jieping Ye

IEEE Trans. Pattern Anal. Mach. Intell., 2013

A Convex Formulation for Learning a Shared Predictive Structure from Multiple Tasks.

Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye

IEEE Trans. Pattern Anal. Mach. Intell., 2013

Modeling disease progression via multi-task learning.

Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye

NeuroImage, 2013

Safe and Efficient Screening For Sparse Support Vector Machine.

Zheng Zhao, Jun Liu

CoRR, 2013

Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods.

Jie Wang, Jun Liu, Jieping Ye

CoRR, 2013

Safe Screening With Variational Inequalities and Its Applicaiton to LASSO.

Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye

CoRR, 2013

Tight frame learning for cardiovascular MRI.

Qiu Wang, Jun Liu, Nirmal Janardhanan, Michael O. Zenge, Edgar Mueller, Mariappan S. Nadar

Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

2012

Sparse methods for biomedical data.

Jieping Ye, Jun Liu

SIGKDD Explor., 2012

Sparse non-negative tensor factorization using columnwise coordinate descent.

Ji Liu, Jun Liu, Peter Wonka, Jieping Ye

Pattern Recognit., 2012

Inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method

Kai Zhang, Liang Lan, Jun Liu, Andreas Rauber, Fabian Moerchen

CoRR, 2012

Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization

Jun Liu, Shuiwang Ji, Jieping Ye

CoRR, 2012

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis.

Daoqiang Zhang, Jun Liu, Dinggang Shen

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Modeling disease progression via fused sparse group lasso.

Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

A sparsity-inducing formulation for evolutionary co-clustering.

Shuiwang Ji, Wenlu Zhang, Jun Liu

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Accelerated singular value thresholding for matrix completion.

Yao Hu, Debing Zhang, Jun Liu, Jieping Ye, Xiaofei He

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Improved Nystrom Low-rank Decomposition with Priors.

Kai Zhang, Liang Lan, Jun Liu, Andreas Rauber

Proceedings of the 29th International Conference on Machine Learning, 2012

The Image Matting Method with Regularized Matte.

Junbin Gao, Manoranjan Paul, Jun Liu

Proceedings of the 2012 IEEE International Conference on Multimedia and Expo, 2012

2011

Projection onto A Nonnegative Max-Heap.

Jun Liu, Liang Sun, Jieping Ye

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A multi-task learning formulation for predicting disease progression.

Jiayu Zhou, Lei Yuan, Jun Liu, Jieping Ye

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2010

Generalized low-rank approximations of matrices revisited.

Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan

IEEE Trans. Neural Networks, 2010

The Group Dantzig Selector.

Han Liu, Jian Zhang, Xiaoye Jiang, Jun Liu

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Efficient L1/Lq Norm Regularization

Jun Liu, Jieping Ye

CoRR, 2010

Fast Overlapping Group Lasso

Jun Liu, Jieping Ye

CoRR, 2010

Moreau-Yosida Regularization for Grouped Tree Structure Learning.

Jun Liu, Jieping Ye

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

An efficient algorithm for a class of fused lasso problems.

Jun Liu, Lei Yuan, Jieping Ye

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Face Liveness Detection from a Single Image with Sparse Low Rank Bilinear Discriminative Model.

Xiaoyang Tan, Yi Li, Jun Liu, Lin Jiang

Proceedings of the Computer Vision - ECCV 2010, 2010

2009

Face recognition under occlusions and variant expressions with partial similarity.

Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Jun Liu

IEEE Trans. Inf. Forensics Secur., 2009

Semi-random subspace method for face recognition.

Yulian Zhu, Jun Liu, Songcan Chen

Image Vis. Comput., 2009

Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization.

Jun Liu, Shuiwang Ji, Jieping Ye

Proceedings of the UAI 2009, 2009

Efficient Recovery of Jointly Sparse Vectors.

Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data.

Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation.

Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Teresa Wu, Jing Li, Eric Reiman, Jieping Ye

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Large-scale sparse logistic regression.

Jun Liu, Jianhui Chen, Jieping Ye

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Learning the Optimal Neighborhood Kernel for Classification.

Jun Liu, Jianhui Chen, Songcan Chen, Jieping Ye

Proceedings of the IJCAI 2009, 2009

Efficient Euclidean projections in linear time.

Jun Liu, Jieping Ye

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

A convex formulation for learning shared structures from multiple tasks.

Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Robust faces manifold modeling: Most expressive Vs. most Sparse criterion.

Xiaoyang Tan, Lishan Qiao, Wenjuan Gao, Jun Liu

Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

2008

Pattern Representation in Feature Extraction and Classifier Design: Matrix Versus Vector.

Zhe Wang, Songcan Chen, Jun Liu, Daoqiang Zhang

IEEE Trans. Neural Networks, 2008

Fractional order singular value decomposition representation for face recognition.

Jun Liu, Songcan Chen, Xiaoyang Tan

Pattern Recognit., 2008

A study on three linear discriminant analysis based methods in small sample size problem.

Jun Liu, Songcan Chen, Xiaoyang Tan

Pattern Recognit., 2008

2007

Comments on "Efficient and Robust Feature Extraction by Maximum Margin Criterion".

Jun Liu, Songcan Chen, Xiaoyang Tan, Daoqiang Zhang

IEEE Trans. Neural Networks, 2007

Efficient Pseudoinverse Linear Discriminant Analysis and its Nonlinear Form for Face Recognition.

Jun Liu, Songcan Chen, Xiaoyang Tan, Daoqiang Zhang

Int. J. Pattern Recognit. Artif. Intell., 2007

Single Image Subspace for Face Recognition.

Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan

Proceedings of the Analysis and Modeling of Faces and Gestures, 2007

2006

Non-iterative generalized low rank approximation of matrices.

Jun Liu, Songcan Chen

Pattern Recognit. Lett., 2006

Discriminant common vectors versus neighbourhood components analysis and Laplacianfaces: A comparative study in small sample size problem.

Jun Liu, Songcan Chen

Image Vis. Comput., 2006

Sub-intrapersonal space analysis for face recognition.

Xiaoyang Tan, Jun Liu, Songcan Chen

Neurocomputing, 2006

Recognition from a Single Sample per Person with Multiple SOM Fusion.

Xiaoyang Tan, Jun Liu, Songcan Chen

Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006

2005

Representing Image Matrices: Eigenimages Versus Eigenvectors.

Daoqiang Zhang, Songcan Chen, Jun Liu

Proceedings of the Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005

Weighted SOM-Face: Selecting Local Features for Recognition from Individual Face Image.

Xiaoyang Tan, Jun Liu, Songcan Chen, Fuyan Zhang

Proceedings of the Intelligent Data Engineering and Automated Learning, 2005

Resampling LDA/QR and PCA+LDA for Face Recognition.

Jun Liu, Songcan Chen

Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005

2004

Making FLDA applicable to face recognition with one sample per person.

Songcan Chen, Jun Liu, Zhi-Hua Zhou

Pattern Recognit., 2004

Progressive Principal Component Analysis.

Jun Liu, Songcan Chen, Zhi-Hua Zhou

Proceedings of the Advances in Neural Networks, 2004