Jieping Ye

Ji Liu, Przemyslaw Musialski, Peter Wonka, Jieping Ye: Tensor Completion for Estimating Missing Values in Visual Data. IEEE Trans. Pattern Anal. Mach. Intell. 35(1): 208-220 (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): 1025-1038 (2013)

Zheng Zhao, Lei Wang, Huan Liu, Jieping Ye: On Similarity Preserving Feature Selection. IEEE Trans. Knowl. Data Eng. 25(3): 619-632 (2013)

Pinghua Gong, Changshui Zhang, Zhaosong Lu, Jianhua Huang, Jieping Ye: A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems. CoRR abs/1303.4434 (2013)

Chao Zhang, Lei Zhang, Jieping Ye: Generalization Bounds for Domain Adaptation. CoRR abs/1304.1574 (2013)

Sudhir Kumar, Kelly Boccia, Michael McCutchan, Jieping Ye: Exploring spatial patterns of gene expression from Fruit Fly embryogenesis on the iPhone. Bioinformatics 28(21): 2847-2848 (2012)

Lei Yuan, Alexander Woodard, Shuiwang Ji, Yuan Jiang, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye: Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval. BMC Bioinformatics 13: 107 (2012)

Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A. Narayan, Jieping Ye: Multi-source feature learning for joint analysis of incomplete multiple heterogeneous neuroimaging data. NeuroImage 61(3): 622-632 (2012)

Ji Liu, Jun Liu, Peter Wonka, Jieping Ye: Sparse non-negative tensor factorization using columnwise coordinate descent. Pattern Recognition 45(1): 649-656 (2012)

Jieping Ye, Jun Liu: Sparse methods for biomedical data. SIGKDD Explorations 14(1): 4-15 (2012)

Rita Chattopadhyay, Mark Jesunathadas, Brach Poston, Marco Santello, Jieping Ye, Sethuraman Panchanathan: A Subject-Independent Method for Automatically Grading Electromyographic Features During a Fatiguing Contraction. IEEE Trans. Biomed. Engineering 59(6): 1749-1757 (2012)

Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, Zhi-Hua Zhou: Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning. IEEE/ACM Trans. Comput. Biology Bioinform. 9(1): 98-112 (2012)

Jianhui Chen, Ji Liu, Jieping Ye: Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks. TKDD 5(4): 22 (2012)

Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye: Multisource domain adaptation and its application to early detection of fatigue. TKDD 6(4): 18 (2012)

Sukru Tikves, Sedat Gokalp, M'hamed H. Temkit, Sujogya Banerjee, Jieping Ye, Hasan Davulcu: Perspective Analysis for Online Debates. ASONAM 2012: 898-905

Debing Zhang, Yao Hu, Jieping Ye, Xuelong Li, Xiaofei He: Matrix completion by Truncated Nuclear Norm Regularization. CVPR 2012: 2192-2199

Yao Hu, Debing Zhang, Jun Liu, Jieping Ye, Xiaofei He: Accelerated singular value thresholding for matrix completion. KDD 2012: 298-306

Shuo Xiang, Yunzhang Zhu, Xiaotong Shen, Jieping Ye: Optimal exact least squares rank minimization. KDD 2012: 480-488

Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye: Batch mode active sampling based on marginal probability distribution matching. KDD 2012: 741-749

Pinghua Gong, Jieping Ye, Changshui Zhang: Robust multi-task feature learning. KDD 2012: 895-903

Sen Yang, Lei Yuan, Ying-Cheng Lai, Xiaotong Shen, Peter Wonka, Jieping Ye: Feature grouping and selection over an undirected graph. KDD 2012: 922-930

Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye: Modeling disease progression via fused sparse group lasso. KDD 2012: 1095-1103

Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A. Narayan, Jieping Ye: Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data. KDD 2012: 1149-1157

Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He: Multi-task Vector Field Learning. NIPS 2012: 296-304

Pinghua Gong, Jieping Ye, Changshui Zhang: Multi-Stage Multi-Task Feature Learning. NIPS 2012: 1997-2005

Chao Zhang, Lei Zhang, Jieping Ye: Generalization Bounds for Domain Adaptation. NIPS 2012

Jun Liu, Shuiwang Ji, Jieping Ye: Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization. CoRR abs/1205.2631 (2012)

Shuo Xiang, Xiaotong Shen, Jieping Ye: Efficient Sparse Group Feature Selection via Nonconvex Optimization. CoRR abs/1205.5075 (2012)

Jianhui Chen, Jieping Ye: Sparse Trace Norm Regularization. CoRR abs/1206.0333 (2012)

Sen Yang, Zhisong Pan, Xiaotong Shen, Peter Wonka, Jieping Ye: Fused Multiple Graphical Lasso. CoRR abs/1209.2139 (2012)

Jie Wang, Binbin Lin, Pinghua Gong, Peter Wonka, Jieping Ye: Lasso Screening Rules via Dual Polytope Projection. CoRR abs/1211.3966 (2012)

Sudhir Kumar, Charlotte Konikoff, Bernard Van Emden, Christopher Busick, Kailah T. Davis, Shuiwang Ji, Lin-Wei Wu, Hector Ramos, Thomas Brody, Sethuraman Panchanathan, Jieping Ye, Timothy L. Karr, Kristyn Gerold, Michael McCutchan, Stuart J. Newfeld: FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis. Bioinformatics 27(23): 3319-3320 (2011)

Jieping Ye, Teresa Wu, Jing Li, Kewei Chen: Machine Learning Approaches for the Neuroimaging Study of Alzheimer's Disease. IEEE Computer 44(4): 99-101 (2011)

Shipeng Yu, Jinbo Bi, Jieping Ye: Matrix-variate and higher-order probabilistic projections. Data Min. Knowl. Discov. 22(3): 372-392 (2011)

Liang Sun, Shuiwang Ji, Jieping Ye: Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 33(1): 194-200 (2011)

Xichuan Zhou, Jieping Ye, Yujie Feng: Tuberculosis Surveillance by Analyzing Google Trends. IEEE Trans. Biomed. Engineering 58(8): 2247-2254 (2011)

Haiqin Yang, Zenglin Xu, Jieping Ye, Irwin King, Michael R. Lyu: Efficient Sparse Generalized Multiple Kernel Learning. IEEE Transactions on Neural Networks 22(3): 433-446 (2011)

Rita Chattopadhyay, Jieping Ye, Sethuraman Panchanathan: Transfer Learning Framework for Early Detection of Fatigue Using Non-invasive Surface Electromyogram Signals (SEMG). AAAI Spring Symposium: Computational Physiology 2011

Jianhui Chen, Jiayu Zhou, Jieping Ye: Integrating low-rank and group-sparse structures for robust multi-task learning. KDD 2011: 42-50

Rita Chattopadhyay, Jieping Ye, Sethuraman Panchanathan, Wei Fan, Ian Davidson: Multi-source domain adaptation and its application to early detection of fatigue. KDD 2011: 717-725

Jiayu Zhou, Lei Yuan, Jun Liu, Jieping Ye: A multi-task learning formulation for predicting disease progression. KDD 2011: 814-822

Shuai Huang, Jing Li, Jieping Ye, Adam Fleisher, Kewei Chen, Teresa Wu, Eric Reiman: Brain effective connectivity modeling for alzheimer's disease by sparse gaussian bayesian network. KDD 2011: 931-939

Lei Yuan, Jun Liu, Jieping Ye: Efficient Methods for Overlapping Group Lasso. NIPS 2011: 352-360

Jun Liu, Liang Sun, Jieping Ye: Projection onto A Nonnegative Max-Heap. NIPS 2011: 487-495

Qian Sun, Rita Chattopadhyay, Sethuraman Panchanathan, Jieping Ye: A Two-Stage Weighting Framework for Multi-Source Domain Adaptation. NIPS 2011: 505-513

Jiayu Zhou, Jianhui Chen, Jieping Ye: Clustered Multi-Task Learning Via Alternating Structure Optimization. NIPS 2011: 702-710

Shuai Huang, Jing Li, Jieping Ye, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman: Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis. NIPS 2011: 1431-1439

Ivaylo Ilinkin, Jieping Ye, Ravi Janardan: Multiple structure alignment and consensus identification for proteins. BMC Bioinformatics 11: 71 (2010)

Shuai Huang, Jing Li, Liang Sun, Jieping Ye, Adam Fleisher, Teresa Wu, Kewei Chen, Eric Reiman: Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation. NeuroImage 50(3): 935-949 (2010)

Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye: Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning. SIAM Journal on Optimization 20(6): 3465-3489 (2010)

Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye: A shared-subspace learning framework for multi-label classification. TKDD 4(2) (2010)

Vineeth Nallure Balasubramanian, Shayok Chakraborty, Sethuraman Panchanathan, Jieping Ye: Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework. ICMLA 2010: 235-242

Liang Sun, Betul Ceran, Jieping Ye: A scalable two-stage approach for a class of dimensionality reduction techniques. KDD 2010: 313-322

Jun Liu, Lei Yuan, Jieping Ye: An efficient algorithm for a class of fused lasso problems. KDD 2010: 323-332

Jianhui Chen, Ji Liu, Jieping Ye: Learning incoherent sparse and low-rank patterns from multiple tasks. KDD 2010: 1179-1188

Ji Liu, Peter Wonka, Jieping Ye: Multi-Stage Dantzig Selector. NIPS 2010: 1450-1458

Jun Liu, Jieping Ye: Moreau-Yosida Regularization for Grouped Tree Structure Learning. NIPS 2010: 1459-1467

Jun Liu, Jieping Ye: Fast Overlapping Group Lasso. CoRR abs/1009.0306 (2010)

Jun Liu, Jieping Ye: Efficient L1/Lq Norm Regularization. CoRR abs/1009.4766 (2010)

Shuiwang Ji, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye: A bag-of-words approach for Drosophila gene expression pattern annotation. BMC Bioinformatics 10 (2009)

Mingrui Wu, Jieping Ye: A Small Sphere and Large Margin Approach for Novelty Detection Using Training Data with Outliers. IEEE Trans. Pattern Anal. Mach. Intell. 31(11): 2088-2092 (2009)

Saif Ali, Jieping Ye, Anshuman Razdan, Peter Wonka: Compressed Facade Displacement Maps. IEEE Trans. Vis. Comput. Graph. 15(2): 262-273 (2009)

Ji Liu, Przemyslaw Musialski, Peter Wonka, Jieping Ye: Tensor completion for estimating missing values in visual data. ICCV 2009: 2114-2121

Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye: A convex formulation for learning shared structures from multiple tasks. ICML 2009: 18

Shuiwang Ji, Jieping Ye: An accelerated gradient method for trace norm minimization. ICML 2009: 58

Jun Liu, Jieping Ye: Efficient Euclidean projections in linear time. ICML 2009: 83

Liang Sun, Shuiwang Ji, Jieping Ye: A least squares formulation for a class of generalized eigenvalue problems in machine learning. ICML 2009: 123

Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King: Non-monotonic feature selection. ICML 2009: 144

Liu Yang, Rong Jin, Jieping Ye: Online learning by ellipsoid method. ICML 2009: 145

Shuiwang Ji, Jieping Ye: Linear Dimensionality Reduction for Multi-label Classification. IJCAI 2009: 1077-1082

Jun Liu, Jianhui Chen, Songcan Chen, Jieping Ye: Learning the Optimal Neighborhood Kernel for Classification. IJCAI 2009: 1144-1149

Liang Sun, Shuiwang Ji, Shipeng Yu, Jieping Ye: On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares. IJCAI 2009: 1230-1235

Lei Tang, Jianhui Chen, Jieping Ye: On Multiple Kernel Learning with Multiple Labels. IJCAI 2009: 1255-1260

Zheng Zhao, Liang Sun, Shipeng Yu, Huan Liu, Jieping Ye: Multiclass Probabilistic Kernel Discriminant Analysis. IJCAI 2009: 1363-1368

Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, Zhi-Hua Zhou: DrosophilaGene Expression Pattern Annotation through Multi-Instance Multi-Label Learning. IJCAI 2009: 1445-1450

Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye: Drosophila gene expression pattern annotation using sparse features and term-term interactions. KDD 2009: 407-416

Jun Liu, Jianhui Chen, Jieping Ye: Large-scale sparse logistic regression. KDD 2009: 547-556

Bao-Hong Shen, Shuiwang Ji, Jieping Ye: Mining discrete patterns via binary matrix factorization. KDD 2009: 757-766

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: 1335-1344

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: 808-816

Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye: Efficient Recovery of Jointly Sparse Vectors. NIPS 2009: 1812-1820

Jun Liu, Shuiwang Ji, Jieping Ye: Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization. UAI 2009: 339-348

Jieping Ye, Ravi Janardan, Sudhir Kumar: Biological Image Analysis via Matrix Approximation. Encyclopedia of Data Warehousing and Mining 2009: 166-170

Qi Li, Jieping Ye, Chandra Kambhamettu: Interest Pixel Mining. Encyclopedia of Data Warehousing and Mining 2009: 1091-1096

Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, Jieping Ye: Automated annotation of Drosophila gene expression patterns using a controlled vocabulary. Bioinformatics 24(17): 1881-1888 (2008)

Liang Sun, Shuiwang Ji, Jieping Ye: Adaptive diffusion kernel learning from biological networks for protein function prediction. BMC Bioinformatics 9 (2008)

Qi Li, Jieping Ye, Min Li, Chandra Kambhamettu: Adaptive Appearance Based Face Recognition. International Journal on Artificial Intelligence Tools 17(1): 175-193 (2008)

Qi Li, Chandra Kambhamettu, Jieping Ye: An evaluation of identity representability of facial expressions using feature distributions. Neurocomputing 71(10-12): 1902-1912 (2008)

Jieping Ye: Comments on the Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion. Journal of Machine Learning Research 9: 517-519 (2008)

Jieping Ye, Shuiwang Ji, Jianhui Chen: Multi-class Discriminant Kernel Learning via Convex Programming. Journal of Machine Learning Research 9: 719-758 (2008)

Qi Li, Jieping Ye, Chandra Kambhamettu: Interest point detection using imbalance oriented selection. Pattern Recognition 41(2): 672-688 (2008)

Jieping Ye, Jianhui Chen, Ravi Janardan, Sudhir Kumar: Developmental stage annotation of Drosophila gene expression pattern images via an entire solution path for LDA. TKDD 2(1) (2008)

Shuiwang Ji, Jieping Ye: Kernel Uncorrelated and Regularized Discriminant Analysis: A Theoretical and Computational Study. IEEE Trans. Knowl. Data Eng. 20(10): 1311-1321 (2008)

Shuiwang Ji, Jieping Ye: Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection. IEEE Transactions on Neural Networks 19(10): 1768-1782 (2008)

Shuiwang Ji, Jieping Ye: A unified framework for generalized Linear Discriminant Analysis. CVPR 2008

Jianhui Chen, Jieping Ye: Training SVM with indefinite kernels. ICML 2008: 136-143

Liang Sun, Shuiwang Ji, Jieping Ye: A least squares formulation for canonical correlation analysis. ICML 2008: 1024-1031

Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Mingrui Wu, Jieping Ye: Learning subspace kernels for classification. KDD 2008: 106-114

Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye: Extracting shared subspace for multi-label classification. KDD 2008: 381-389

Liang Sun, Shuiwang Ji, Jieping Ye: Hypergraph spectral learning for multi-label classification. KDD 2008: 668-676

Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Yung Chang: Identifying biologically relevant genes via multiple heterogeneous data sources. KDD 2008: 839-847

Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng Zhao, Rinkal Patel, Min Bae, Ravi Janardan, Huan Liu, Gene E. Alexander, Eric Reiman: Heterogeneous data fusion for alzheimer's disease study. KDD 2008: 1025-1033

Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye: Multi-label Multiple Kernel Learning. NIPS 2008: 777-784

M. Arif Wani, Mehmed M. Kantardzic, Tao Li, Ying Liu, Lukasz A. Kurgan, Jieping Ye, Mitsunori Ogihara, Seref Sagiroglu, Xue-wen Chen, Leif E. Peterson, Khalid Hafeez (Eds.): The Sixth International Conference on Machine Learning and Applications, ICMLA 2007, Cincinnati, Ohio, USA, 13-15 December 2007. IEEE Computer Society 2008, isbn 0-7695-3069-9

Jieping Ye, Tao Xiong: SVM versus Least Squares SVM. Journal of Machine Learning Research - Proceedings Track 2: 644-651 (2007)

Vineeth Nallure Balasubramanian, Jieping Ye, Sethuraman Panchanathan: Biased Manifold Embedding: A Framework for Person-Independent Head Pose Estimation. CVPR 2007

Jianhui Chen, Jieping Ye, Qi Li: Integrating Global and Local Structures: A Least Squares Framework for Dimensionality Reduction. CVPR 2007

Jieping Ye, Zheng Zhao, Huan Liu: Adaptive Distance Metric Learning for Clustering. CVPR 2007

Jieping Ye: Least squares linear discriminant analysis. ICML 2007: 1087-1093

Jieping Ye, Jianhui Chen, Shuiwang Ji: Discriminant kernel and regularization parameter learning via semidefinite programming. ICML 2007: 1095-1102

Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu: Nonlinear adaptive distance metric learning for clustering. KDD 2007: 123-132

Jieping Ye, Shuiwang Ji, Jianhui Chen: Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming. KDD 2007: 854-863

Jieping Ye, Zheng Zhao, Mingrui Wu: Discriminative K-means for Clustering. NIPS 2007

Jieping Ye, Tao Xiong: Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis. Journal of Machine Learning Research 7: 1183-1204 (2006)

Qi Li, Jieping Ye, Chandra Kambhamettu: Spatial interest pixels (SIPs): useful low-level features of visual media data. Multimedia Tools Appl. 30(1): 89-108 (2006)

Jieping Ye, Ravi Janardan, Qi Li, Haesun Park: Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis. IEEE Trans. Knowl. Data Eng. 18(10): 1312-1322 (2006)

Jieping Ye, Tao Xiong, Qi Li, Ravi Janardan, Jinbo Bi, Vladimir Cherkassky, Chandra Kambhamettu: Efficient model selection for regularized linear discriminant analysis. CIKM 2006: 532-539

Tao Xiong, Jieping Ye, Vladimir Cherkassky: Kernel Uncorrelated and Orthogonal Discriminant Analysis: A Unified Approach. CVPR (1) 2006: 125-131

Jieping Ye, Tao Xiong: Null space versus orthogonal linear discriminant analysis. ICML 2006: 1073-1080

Qi Li, Jieping Ye, Min Li, Chandra Kambhamettu: Adaptive Appearance Based Face Recognition. ICTAI 2006: 677-684

Jieping Ye, Tie Wang: Regularized discriminant analysis for high dimensional, low sample size data. KDD 2006: 454-463

Jieping Ye, Tao Xiong, Ravi Janardan: CPM: A Covariance-preserving Projection Method. SDM 2006

Jieping Ye, Ivaylo Ilinkin, Ravi Janardan, Adam Isom: Multiple Structure Alignment and Consensus Identification for Proteins. WABI 2006: 115-125

M. Arif Wani, Tao Li, Lukasz A. Kurgan, Jieping Ye, Ying Liu (Eds.): The Fifth International Conference on Machine Learning and Applications, ICMLA 2006, Orlando, Florida, USA, 14-16 December 2006. IEEE Computer Society 2006, isbn 0-7695-2735-3

Jieping Ye: Characterization of a Family of Algorithms for Generalized Discriminant Analysis on Undersampled Problems. Journal of Machine Learning Research 6: 483-502 (2005)

Jieping Ye: Generalized Low Rank Approximations of Matrices. Machine Learning 61(1-3): 167-191 (2005)

Jieping Ye, Qi Li: A Two-Stage Linear Discriminant Analysis via QR-Decomposition. IEEE Trans. Pattern Anal. Mach. Intell. 27(6): 929-941 (2005)

Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Janardan, Vipin Kumar: IDR/QR: An Incremental Dimension Reduction Algorithm via QR Decomposition. IEEE Trans. Knowl. Data Eng. 17(9): 1208-1222 (2005)

Chris H. Q. Ding, Jieping Ye: 2-Dimensional Singular Value Decomposition for 2D Maps and Images. SDM 2005

Jieping Ye, Ravi Janardan, Songtao Liu: Pairwise Protein Structure Alignment Based on an Orientation-independent Backbone Representation. J. Bioinformatics and Computational Biology 2(4): 699-718 (2004)

Jieping Ye, Ravi Janardan: Approximate Multiple Protein Structure Alignment Using the Sum-of-Pairs Distance. Journal of Computational Biology 11(5): 986-1000 (2004)

Jieping Ye, Ravi Janardan, Cheong Hee Park, Haesun Park: An Optimization Criterion for Generalized Discriminant Analysis on Undersampled Problems. IEEE Trans. Pattern Anal. Mach. Intell. 26(8): 982-994 (2004)

Jieping Ye, Qi Li: LDA/QR: an efficient and effective dimension reduction algorithm and its theoretical foundation. Pattern Recognition 37(4): 851-854 (2004)

Jieping Ye, Tao Li, Tao Xiong, Ravi Janardan: Using Uncorrelated Discriminant Analysis for Tissue Classification with Gene Expression Data. IEEE/ACM Trans. Comput. Biology Bioinform. 1(4): 181-190 (2004)

Qi Li, Jieping Ye, Chandra Kambhamettu: Linear Projection Methods in Face Recognition under Unconstrained Illuminations: A Comparative Study. CVPR (2) 2004: 474-481

Jieping Ye: Generalized low rank approximations of matrices. ICML 2004

Jieping Ye, Ravi Janardan, Qi Li, Haesun Park: Feature extraction via generalized uncorrelated linear discriminant analysis. ICML 2004

Jieping Ye, Ravi Janardan, Qi Li: GPCA: an efficient dimension reduction scheme for image compression and retrieval. KDD 2004: 354-363

Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Janardan, Vipin Kumar: IDR/QR: an incremental dimension reduction algorithm via QR decomposition. KDD 2004: 364-373

Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladimir Cherkassky: Efficient Kernel Discriminant Analysis via QR Decomposition. NIPS 2004

Jieping Ye, Ravi Janardan, Qi Li: Two-Dimensional Linear Discriminant Analysis. NIPS 2004

Qi Li, Jieping Ye, Chandra Kambhamettu: Spatial Interest Pixels (SIPs): Useful Low-Level Features of Visual Media Data. ICDM 2003: 163-170

Jieping Ye, Ravi Janardan, Cheong Hee Park, Haesun Park: A new optimization criterion for generalized discriminant analysis on undersampled problems. ICDM 2003: 419-426

Jieping Ye, Ravi Janardan, Songtao Liu: Pairwise Protein Structure Alignment Based on an Orientation-Independent Representation of the Backbone Geometry. ICTAI 2003: 2-8

Ruibin Qu, Jieping Ye: Approximation of minimum energy curves. Applied Mathematics and Computation 108(2-3): 153-166 (2000)

Ruibin Qu, Jieping Ye: Efficient approximation of minimum energy curves with interpolatory constraints. Applied Mathematics and Computation 109(2-3): 151-166 (2000)