2009
·
Liang
Sun, Jun Liu, Jianhui Chen, and Jieping
Ye. Efficient Recovery of Jointly Sparse Vectors. The Twenty-Third Annual Conference on Neural Information
Processing Systems (NIPS 2009). PDF
·
Shui
Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei
Chen, Adam Fleisher, Eric Reiman, and Jieping Ye. Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data. The Twenty-Third Annual Conference on
Neural Information Processing Systems (NIPS 2009). PDF
·
Ji Liu, Przem Musialski, Peter Wonka, and Jieping Ye. Tensor
completion for estimating missing values in visual data. The Twelfth
IEEE International Conference on Computer Vision (ICCV
2009). PDF
VIDEO
·
Jun Liu,
Shuiwang Ji, and Jieping Ye. Multi-task Feature Learning via Efficient L2,1-Norm
Minimization. The Twenty-fifth Conference
on Uncertainty in Artificial Intelligence (UAI 2009). PDF CODE
·
Liang
Sun, Rinkal Patel, Jun Liu, Kewei
Chen, Teresa Wu, Jing Li, Eric Reiman, and Jieping Ye. Mining Brain Region Connectivity for
Alzheimer's Disease Study via Sparse Inverse
Covariance Estimation. The Fifteenth ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (SIGKDD
2009), pp. 1335-1344. Full Presentation. PDF
·
Bao-Hong Shen, Shuiwang Ji, and Jieping Ye. Mining
Discrete Patterns via Binary Matrix Factorization. The Fifteenth ACM SIGKDD
International Conference On Knowledge Discovery and
Data Mining (SIGKDD 2009), pp. 757-766. Full Presentation. PDF
CODE
·
Jun Liu,
Jianhui Chen, and Jieping
Ye. Large-Scale Sparse Logistic Regression. The Fifteenth ACM SIGKDD
International Conference On Knowledge Discovery and
Data Mining (SIGKDD 2009), pp. 547-556. Full Presentation. PDF
CODE
·
Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, and Jieping
Ye. Drosophila Gene Expression Pattern Annotation Using Sparse Features and
Term-term Interactions. The Fifteenth ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (SIGKDD
2009), pp. 407-416. Short
Presentation. PDF CODE
·
Jianhui Chen, Lei
Tang, Jun Liu, and Jieping Ye. A Convex Formulation
for Learning Shared Structures from Multiple Tasks. The Twenty-Sixth International Conference on Machine Learning (ICML 2009). PDF
·
Liang
Sun, Shuiwang Ji, and Jieping Ye. A Least Squares Formulation for a Class of
Generalized Eigenvalue Problems in Machine Learning. The Twenty-Sixth International Conference on
Machine Learning (ICML 2009).
PDF
·
Shuiwang Ji and Jieping Ye. An Accelerated Gradient Method for Trace Norm
Minimization. The Twenty-Sixth
International Conference on Machine Learning (ICML 2009). PDF CODE
·
Jun Liu
and Jieping Ye. Efficient Euclidean Projections in
Linear Time. The Twenty-Sixth
International Conference on Machine Learning (ICML 2009). PDF CODE
·
Zenglin
Xu, Rong Jin, Jieping
Ye, Michael R. Lyu, and Irwin King. Non-Monotonic
Feature Selection. The Twenty-Sixth
International Conference on Machine Learning (ICML 2009). PDF
·
Liu
Yang, Rong Jin, and Jieping
Ye. Online Learning by Ellipsoid Method. The
Twenty-Sixth International Conference on Machine Learning (ICML 2009). PDF
·
Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, and
Zhi-Hua Zhou.
Drosophila Gene Expression Pattern Annotation Through
Multi-Instance Multi-Label Learning. The
Twenty-first International Joint Conference on Artificial Intelligence (IJCAI 2009). PDF
·
Jun Liu,
Jianhui Chen, Songcan Chen,
and Jieping Ye. Learning the Optimal Neighborhood
Kernel for Classification. The
Twenty-first International Joint Conference on Artificial Intelligence (IJCAI 2009). PDF
·
Liang
Sun, Shuiwang Ji, Shipeng Yu, and Jieping Ye. On
the Equivalence Between Canonical Correlation Analysis and Orthonormalized
Partial Least Squares. The Twenty-first
International Joint Conference on Artificial Intelligence (IJCAI 2009). PDF
·
Zheng Zhao, Liang
Sun, Shipeng Yu, Huan Liu,
and Jieping Ye. Multiclass Probabilistic Kernel Discriminant Analysis. The
Twenty-first International Joint Conference on Artificial Intelligence (IJCAI 2009). PDF
·
Lei
Tang, Jianhui Chen, and Jieping
Ye. On Multiple Kernel Learning with Multiple Labels. The Twenty-first International Joint Conference on Artificial
Intelligence (IJCAI 2009).
PDF
·
Shuiwang Ji and Jieping Ye. Linear
Dimensionality Reduction for Multi-label Classification. The Twenty-first International Joint Conference on Artificial
Intelligence (IJCAI 2009).
PDF
·
Ting Kei
Pong, Paul Tseng, Shuiwang Ji,
and Jieping Ye. Trace Norm Regularization: Reformulations, Algorithms, and Multi-task
Learning. Submitted to SIAM Journal on Optimization,
June 2009. PDF
CODE
·
Shuiwang Ji, Lei Tang, Shipeng
Yu, and Jieping Ye. A Shared-subspace Learning
Framework for Multi-label Classification. ACM Transactions on Knowledge Discovery from
Data. In
press. PDF
·
Shuiwang Ji, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, and Jieping
Ye. A bag-of-words approach for Drosophila gene expression pattern
annotation. BMC
Bioinformatics, 2009, 10:119. PDF
·
Mingrui Wu and Jieping Ye. A Small Sphere and Large Margin Approach for Novelty
Detection Using Training Data with Outliers. IEEE Transactions on Pattern
Analysis and Machine Intelligence. In press. PDF
· Saif Ali, Jieping Ye, Anshuman Razdan, Peter Wonka. Compressed Facade Displacement Mapping. IEEE Transactions on Visualization and Computer Graphics. Vol. 15, No. 2, pp. 262-273, 2009. PDF
2008
·
Shuiwang Ji, Liang Sun, Rong Jin, and Jieping Ye. Multi-label Multiple Kernel Learning. The Twenty-Second
Annual Conference on Neural Information Processing Systems (NIPS 2008). PDF
·
Jieping Ye et al. Heterogeneous data fusion for
Alzheimer's disease study. The
Fourteenth ACM SIGKDD International Conference On
Knowledge Discovery and Data Mining (SIGKDD
2008), pp. 1025-1033. PDF
·
Shuiwang Ji, Lei Tang, Shipeng Yu, and Jieping Ye. Extracting Shared Subspace for Multi-label
Classification. The
Fourteenth ACM SIGKDD International Conference On
Knowledge Discovery and Data Mining (SIGKDD
2008), pp. 381-389. PDF
·
Liang
Sun, Shuiwang Ji, and Jieping Ye. Hypergraph Spectral
Learning for Multi-label Classification. The Fourteenth ACM SIGKDD International Conference On
Knowledge Discovery and Data Mining (SIGKDD
2008), pp. 668-676. PDF
·
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Mingrui Wu, and Jieping Ye.
Learning Subspace Kernels for Classification. The Fourteenth ACM SIGKDD International Conference On
Knowledge Discovery and Data Mining (SIGKDD
2008), pp. 106-114. PDF
·
Zheng Zhao, Jiangxin Wang, Huan Liu,
Jieping Ye, and Yung Chang. Identifying Biologically Relevant Genes via
Multiple Heterogeneous Data Sources. The Fourteenth ACM SIGKDD International Conference On
Knowledge Discovery and Data Mining (SIGKDD
2008), pp. 839-847. PDF
· Liang Sun, Shuiwang Ji, and Jieping Ye. A least squares formulation for canonical correlation analysis. The Twenty-Fifth International Conference on Machine Learning (ICML 2008), pp. 1024-1031. PDF
·
·
·
Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, and Jieping Ye. Automated
annotation of Drosophila gene
expression patterns using a controlled vocabulary. Bioinformatics. 24(17):1881-1888, 2008. PDF
·
·
· Jieping Ye, Shuiwang Ji, and Jianhui Chen. Multi-class Discriminant Kernel Learning via Convex Programming. Journal of Machine Learning Research. 9(Apr):719-758. PDF
· Shuiwang Ji and Jieping Ye. Kernel Uncorrelated and Regularized Discriminant Analysis: A Theoretical and Computational
Study. IEEE
Transactions on Knowledge and Data Engineering. Vol. 20, No. 10,
pp. 1311-1321, 2008. PDF
·
2007
·
·
·
·
·
·
·
Vineeth Nallure,
·
·
2006
·
Jieping Ye et al. Efficient model selection for
regularized linear discriminant analysis. The
Fifteenth ACM International Conference on Information and Knowledge Management
(CIKM 2006), pp. 532–539. PDF
·
·
Jieping Ye and Tie Wang. Regularized
(Quadratic) Discriminant Analysis for high
dimensional, low sample size data. The Twelfth ACM SIGKDD International
Conference On Knowledge Discovery and Data Mining
(SIGKDD 2006), pp. 454—463.
PDF
· Jieping Ye, Jianhui Chen, Qi Li, and Sudhir Kumar. Classification of Drosophila embryonic developmental stage range based on gene expression pattern images. Computational Systems Bioinformatics Conference (CSB 2006), pp. 293—298. PDF
·
Jieping Ye and Tao Xiong.
Null space versus orthogonal linear discriminant
analysis. The Twenty-Third International
Conference on Machine Learning (ICML 2006), pp 1073—1080. PDF
·
Jieping Ye, Tao Xiong,
and Ravi Janardan. CPM: A covariance-preserving projection
method. The Sixth SIAM
International Conference on Data Mining (SDM 2006), pp. 24—34.
PDF
· Tao Xiong, Jieping Ye, and Vladimir Cherkassky. Kernel Uncorrelated and Orthogonal Discriminant Analysis: A Unified Approach. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), pp. 125—131. PDF
· Jieping Ye, Ravi Janardan, Qi Li, and Haesun Park. Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis. IEEE Transactions on Knowledge and Data Engineering. Vol. 18, No. 10, pp. 1312—1322, 2006. PDF
· Jieping Ye and Tao Xiong. Computational and theoretical analysis of null space and orthogonal linear discriminant analysis. Journal of Machine Learning Research. 7(July): 1183—1204, 2006. PDF
· Qi Li, Jieping Ye, and Chandra Kambhamettu. Spatial Interest Pixels (SIPs): Useful Low-Level Features of Visual Media Data. Journal of Multimedia Tools and Applications. Vol. 30, No. 1, pp. 89—108, 2006. PDF
2005
·
Chris Ding and Jieping Ye.
2-Dimensional Singular Value Decomposition for 2D Maps and
Images. Proceedings of the SIAM International
Conference on Data Mining (SDM
2005), pp. 24—34.
PDF
·
Jieping Ye.
Characterization of a Family of Algorithms for
Generalized Discriminant Analysis on Undersampled Problems. Journal of Machine Learning
Research. 6(Apr): 483—502, 2005. PDF
·
Jieping Ye, Qi
Li, Hui Xiong, Haesun Park, Ravi Janardan, and Vipin Kumar. IDR/QR: An Incremental Dimension
Reduction Algorithm via QR Decomposition. IEEE
Transactions on Knowledge and Data Engineering. Special Issue on Intelligent Data Preparation. Vol. 17, No. 9, pp. 1208—1222,
2005. PDF
·
Jieping Ye.
Generalized Low Rank Approximations of Matrices. Machine
Learning Journal. Vol. 61, pp. 167—191, 2005. PDF
·
Jieping Ye and Qi
Li. A two-stage linear discriminant analysis via QR decomposition. IEEE
Transactions on Pattern Analysis and Machine Intelligence. Vol. 27, No. 6, pp. 929—941, 2005. PDF
2004
· Jieping Ye, Ravi Janardan, and Qi Li. Two-Dimensional Linear Discriminant Analysis. The Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), pp. 1569—1576. PDF
· Xiong Tao, Jieping Ye, Qi Li, Ravi Janardan, and Vladimir Cherkassky. Efficient Kernel Discriminant Analysis via QR Decomposition. The Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), pp. 1529—1536. PDF
·
· Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Janardan, and Vipin Kumar. IDR/QR: An Incremental Dimension Reduction Algorithm via QR Decomposition. The Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD 2004), pp. 364—373. PDF
· Jieping Ye, Ravi Janardan, Qi Li, and Haesun Park. Feature Extraction via Generalized Uncorrelated Linear Discriminant Analysis. The Twenty-First International Conference on Machine Learning (ICML 2004), pp. 895—902. PDF
· Jieping Ye. Generalized Low Rank Approximations of Matrices. The Twenty-First International Conference on Machine Learning (ICML 2004), pp. 887—894. Outstanding Student Paper Award PDF
· Qi Li, Jieping Ye, and Chandra Kambhamettu. Linear Projection Methods in Face Recognition under Unconstrained Illumination: A Comparative Study. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2004). PDF
· Jieping Ye, Tao Li, Tao Xiong, and Ravi Janardan. Using Uncorrelated Discriminant Analysis for Tissue Classification with Gene Expression Data. [Datasets] IEEE/ACM Transactions on Computational Biology and Bioinformatics. Vol. 1, No. 4, pp. 181—190, 2004. PDF
· Jieping Ye, Ravi Janardan, and Songtao Liu. Pairwise protein structure alignment based on an orientation independent representation of the backbone geometry. [Color Figures] [Software & Test Data] Journal of Bioinformatics and Computational Biology. Vol. 2, No. 4, pp. 699—717, 2004. PDF
· Jieping Ye, Ravi Janardan, Cheonghee Park, and Haesun Park. An optimization criterion for generalized discriminant analysis on undersampled problems. [Color Figures] [Datasets] IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 26, No. 8, pp. 982—994, 2004. PDF
· Jieping Ye and Ravi Janardan. Approximate multiple protein structure alignment using the Sum-of-Pairs distance. [Color Figures] Journal of Computational Biology. Vol. 11, No. 5, pp. 986—1000, 2004. PDF
2003
· Jieping Ye, Ravi Janardan, Cheonghee Park, and Haesun Park. A new optimization criterion for generalized discriminant analysis on undersampled problem. The Third IEEE International Conference on Data Mining (ICDM 2003), pp. 419—426. PDF
· Qi Li, Jieping Ye, and Chandra Kambhamettu. Spatial Interest Pixels (SIPs): Useful Low-Level Features of Visual Media Data. The Third IEEE International Conference on Data Mining (ICDM 2003), pp. 163—170. PDF
·
Jieping Ye, Ravi Janardan,
and Songtao Liu. Pairwise
protein structure alignment based on an orientation-independent representation
of the backbone geometry. The Fifteenth IEEE International
Conference on Tools with Artificial Intelligence (ICTAI 2003), pp. 2—8. PDF
Book Chapters
· Jieping Ye and Shuiwang Ji. Discriminant Analysis for Dimensionality Reduction: An Overview of Recent Developments. In Biometrics: Theory, Methods & Applications, edited by N. V. Boulgouris, K.N. Plataniotis, and E.Micheli-Tzanakou, IEEE/Wiley. (In press) PDF
·
Jieping Ye,