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2010 – today
- 2019
[j92]Wei Zhang, Jinglei Lv, Xiang Li, Dajiang Zhu, Xi Jiang, Shu Zhang, Yu Zhao, Lei Guo, Jieping Ye, Dewen Hu, Tianming Liu:
Experimental Comparisons of Sparse Dictionary Learning and Independent Component Analysis for Brain Network Inference From fMRI Data. IEEE Trans. Biomed. Engineering 66(1): 289-299 (2019)- [i39]Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin:
Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee. CoRR abs/1901.11149 (2019) - [i38]Minne Li, Zhiwei Qin, Yan Jiao, Yaodong Yang, Zhichen Gong, Jun Wang, Chenxi Wang, Guobin Wu, Jieping Ye:
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning. CoRR abs/1901.11454 (2019) - 2018
- [j91]Shaogang Ren, Shuai Huang, Jieping Ye, Xiaoning Qian:
Safe Feature Screening for Generalized LASSO. IEEE Trans. Pattern Anal. Mach. Intell. 40(12): 2992-3006 (2018) - [j90]Libin Zheng, Lei Chen, Jieping Ye:
Order Dispatch in Price-aware Ridesharing. PVLDB 11(8): 853-865 (2018) - [j89]Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Jieping Ye, Ke Xu:
A Unified Approach to Route Planning for Shared Mobility. PVLDB 11(11): 1633-1646 (2018) - [j88]Bashar Haddad, Sen Yang, Lina J. Karam, Jieping Ye, Nital S. Patel, Martin W. Braun:
Multifeature, Sparse-Based Approach for Defects Detection and Classification in Semiconductor Units. IEEE Trans. Automation Science and Engineering 15(1): 145-159 (2018) - [j87]Lu Lin, Jianxin Li, Feng Chen, Jieping Ye, Jinpeng Huai:
Road Traffic Speed Prediction: A Probabilistic Model Fusing Multi-Source Data. IEEE Trans. Knowl. Data Eng. 30(7): 1310-1323 (2018) - [j86]Weizhong Zhang, Tingjin Luo, Shuang Qiu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang:
Identifying Genetic Risk Factors for Alzheimer's Disease via Shared Tree-Guided Feature Learning Across Multiple Tasks. IEEE Trans. Knowl. Data Eng. 30(11): 2145-2156 (2018) - [c188]Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, Jieping Ye, Zhenhui Li:
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction. AAAI 2018: 2588-2595 - [c187]Tieliang Gong, Guangtao Wang, Jieping Ye, Zongben Xu, Ming Lin:
Margin Based PU Learning. AAAI 2018: 3037-3044 - [c186]Ishan Jindal, Zhiwei (Tony) Qin, Xuewen Chen, Matthew S. Nokleby, Jieping Ye:
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. BigData 2018: 1417-1426 - [c185]Carl Yang, Chao Zhang, Xuewen Chen, Jieping Ye, Jiawei Han:
Did You Enjoy the Ride? Understanding Passenger Experience via Heterogeneous Network Embedding. ICDE 2018: 1392-1403 - [c184]
- [c183]Zhaodong Wang, Zhiwei Qin, Xiaocheng Tang, Jieping Ye, Hongtu Zhu:
Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching. ICDM 2018: 617-626 - [c182]Jie Zhang, Yanshuai Tu, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Multi-task sparse screening for predicting future clinical scores using longitudinal cortical thickness measures. ISBI 2018: 1406-1410 - [c181]
- [c180]Zhe Xu, Zhixin Li, Qingwen Guan, Dingshui Zhang, Qiang Li, Junxiao Nan, Chunyang Liu, Wei Bian, Jieping Ye:
Large-Scale Order Dispatch in On-Demand Ride-Hailing Platforms: A Learning and Planning Approach. KDD 2018: 905-913 - [c179]Yaguang Li, Kun Fu, Zheng Wang, Cyrus Shahabi, Jieping Ye, Yan Liu:
Multi-task Representation Learning for Travel Time Estimation. KDD 2018: 1695-1704 - [c178]
- [c177]Chen Luo, Zhengzhang Chen, Lu An Tang, Anshumali Shrivastava, Zhichun Li, Haifeng Chen, Jieping Ye:
TINET: Learning Invariant Networks via Knowledge Transfer. KDD 2018: 1890-1899 - [c176]Zhiwei (Tony) Qin, Chengxiang Zhuo, Wei Tan, Jun Xie, Jieping Ye:
Large-Scale Targeted Marketing by Supervised PageRank with Seeds. MLDM (2) 2018: 409-424 - [c175]Yan Li, Tao Yang, Jiayu Zhou, Jieping Ye:
Multi-Task Learning based Survival Analysis for Predicting Alzheimer's Disease Progression with Multi-Source Block-wise Missing Data. SDM 2018: 288-296 - [c174]Lingyu Zhang, Wei Ai, Chuan Yuan, Yuhui Zhang, Jieping Ye:
Taxi or Hitchhiking: Predicting Passenger's Preferred Service on Ride Sharing Platforms. SIGIR 2018: 1041-1044 - [c173]
- [c172]Yongxin Tong, Libin Wang, Zimu Zhou, Lei Chen, Bowen Du, Jieping Ye:
Dynamic Pricing in Spatial Crowdsourcing: A Matching-Based Approach. SIGMOD Conference 2018: 773-788 - [i37]Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, Jieping Ye, Zhenhui Li:
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction. CoRR abs/1802.08714 (2018) - [i36]Shupeng Gui, Xiangliang Zhang, Shuang Qiu, Mingrui Wu, Jieping Ye, Ji Liu:
GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning. CoRR abs/1805.11182 (2018) - [i35]Ishan Jindal, Zhiwei (Tony) Qin, Xuewen Chen, Matthew S. Nokleby, Jieping Ye:
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. CoRR abs/1811.04345 (2018) - 2017
- [j85]Jinglei Lv, Binbin Lin, Qingyang Li, Wei Zhang, Yu Zhao, Xi Jiang, Lei Guo, Junwei Han, Xintao Hu, Christine Cong Guo, Jieping Ye, Tianming Liu:
Task fMRI data analysis based on supervised stochastic coordinate coding. Medical Image Analysis 38: 1-16 (2017) - [j84]Yongxin Tong, Libin Wang, Zimu Zhou, Bolin Ding, Lei Chen, Jieping Ye, Ke Xu:
Flexible Online Task Assignment in Real-Time Spatial Data. PVLDB 10(11): 1334-1345 (2017) - [j83]Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Feature Constrained Multi-Task Learning Models for Spatiotemporal Event Forecasting. IEEE Trans. Knowl. Data Eng. 29(5): 1059-1072 (2017) - [c171]
- [c170]Lu Wang, Yan Li, Jiayu Zhou, Dongxiao Zhu, Jieping Ye:
Multi-task Survival Analysis. ICDM 2017: 485-494 - [c169]Guangtao Wang, Jiayu Zhou, Jingjie Ni, Tingjin Luo, Wei Long, Hai Zhen, Gao Cong, Jieping Ye:
Robust Self-Tuning Sparse Subspace Clustering. ICDM Workshops 2017: 858-865 - [c168]Weizhong Zhang, Bin Hong, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang:
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction. ICML 2017: 4016-4025 - [c167]Jie Zhang, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Multi-source Multi-target Dictionary Learning for Prediction of Cognitive Decline. IPMI 2017: 184-197 - [c166]Yu Zhao, Xiang Li, Milad Makkie, Shannon Quinn, Binbin Lin, Jieping Ye, Tianming Liu:
Template-guided Functional Network Identification via Supervised Dictionary Learning. ISBI 2017: 72-76 - [c165]Jie Zhang, Yonghui Fan, Qingyang Li, Paul M. Thompson, Jieping Ye, Yalin Wang:
Empowering cortical thickness measures in clinical diagnosis of Alzheimer's disease with spherical sparse coding. ISBI 2017: 446-450 - [c164]Tingjin Luo, Weizhong Zhang, Shang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye, Jie Wang:
Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning. KDD 2017: 345-354 - [c163]Kai Zhang, Chuanren Liu, Jie Zhang, Hui Xiong, Eric P. Xing, Jieping Ye:
Randomization or Condensation?: Linear-Cost Matrix Sketching Via Cascaded Compression Sampling. KDD 2017: 615-623 - [c162]Yongxin Tong, Yuqiang Chen, Zimu Zhou, Lei Chen, Jie Wang, Qiang Yang, Jieping Ye, Weifeng Lv:
The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms. KDD 2017: 1653-1662 - [c161]Lingyu Zhang, Tao Hu, Yue Min, Guobin Wu, Junying Zhang, Pengcheng Feng, Pinghua Gong, Jieping Ye:
A Taxi Order Dispatch Model based On Combinatorial Optimization. KDD 2017: 2151-2159 - [c160]Xiang Li, Aoxiao Zhong, Ming Lin, Ning Guo, Mu Sun, Arkadiusz Sitek, Jieping Ye, James Thrall, Quanzheng Li:
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis. MLMI@MICCAI 2017: 212-219 - [c159]Zhi Nie, Binbin Lin, Shuai Huang, Naren Ramakrishnan, Wei Fan, Jieping Ye:
Pruning Decision Trees via Max-Heap Projection. SDM 2017: 10-18 - [c158]Yashu Liu, Shuang Qiu, Ping Zhang, Pinghua Gong, Fei Wang, Guoliang Xue, Jieping Ye:
Computational Drug Discovery with Dyadic Positive-Unlabeled Learning. SDM 2017: 45-53 - [i34]Shuang Qiu, Tingjin Luo, Jieping Ye, Ming Lin:
Nonconvex One-bit Single-label Multi-label Learning. CoRR abs/1703.06104 (2017) - [i33]Qingyang Li, Dajiang Zhu, Jie Zhang, Derrek Paul Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang:
Large-scale Feature Selection of Risk Genetic Factors for Alzheimer's Disease via Distributed Group Lasso Regression. CoRR abs/1704.08383 (2017) - [i32]Hemanth Venkateswara, Prasanth Lade, Jieping Ye, Sethuraman Panchanathan:
Coupled Support Vector Machines for Supervised Domain Adaptation. CoRR abs/1706.07525 (2017) - [i31]Hemanth Venkateswara, Prasanth Lade, Binbin Lin, Jieping Ye, Sethuraman Panchanathan:
Efficient Approximate Solutions to Mutual Information Based Global Feature Selection. CoRR abs/1706.07535 (2017) - [i30]Xiang Li, Aoxiao Zhong, Ming Lin, Ning Guo, Mu Sun, Arkadiusz Sitek, Jieping Ye, James Thrall, Quanzheng Li:
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis. CoRR abs/1707.06145 (2017) - [i29]Milad Makkie, Xiang Li, Binbin Lin, Jieping Ye, Mojtaba Sedigh Fazli, Tianming Liu, Shannon Quinn:
Distributed rank-1 dictionary learning: Towards fast and scalable solutions for fMRI big data analytics. CoRR abs/1708.02638 (2017) - [i28]Jie Zhang, Qingyang Li, Richard J. Caselli, Jieping Ye, Yalin Wang:
Multi-task Dictionary Learning based Convolutional Neural Network for Computer aided Diagnosis with Longitudinal Images. CoRR abs/1709.00042 (2017) - [i27]Tao Yang, Paul M. Thompson, Sihai Zhao, Jieping Ye:
Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure. CoRR abs/1709.03645 (2017) - [i26]Ishan Jindal, Tony Qin, Xuewen Chen, Matthew S. Nokleby, Jieping Ye:
A Unified Neural Network Approach for Estimating Travel Time and Distance for a Taxi Trip. CoRR abs/1710.04350 (2017) - 2016
- [j82]Kefei Liu, Lei Huang, Hing-Cheung So, Jieping Ye:
Multidimensional folding for sinusoidal order selection. Digital Signal Processing 48: 349-360 (2016) - [j81]Kefei Liu, João Paulo C. L. da Costa, Hing-Cheung So, Lei Huang, Jieping Ye:
Detection of number of components in CANDECOMP/PARAFAC models via minimum description length. Digital Signal Processing 51: 110-123 (2016) - [j80]Zhenfeng Zhu, Jian Cheng, Yao Zhao, Jieping Ye:
LSSLP - Local structure sensitive label propagation. Inf. Sci. 332: 19-32 (2016) - [j79]Lei Wang, Ce Zhu, Jieping Ye, Juergen Gall:
Guest Editors' Introduction: Special issue on deep learning with applications to visual representation and analysis. Sig. Proc.: Image Comm. 47: 463-464 (2016) - [j78]Yashu Liu, Jie Wang, Jieping Ye:
An Efficient Algorithm For Weak Hierarchical Lasso. TKDD 10(3): 32:1-32:24 (2016) - [j77]Pei Yang, Hongxia Yang, Haoda Fu, Dawei Zhou, Jieping Ye, Theodoros Lappas, Jingrui He:
Jointly Modeling Label and Feature Heterogeneity in Medical Informatics. TKDD 10(4): 39:1-39:25 (2016) - [c157]Milad Makkie, Xiang Li, Tianming Liu, Shannon Quinn, Binbin Lin, Jieping Ye:
Distributed rank-1 dictionary learning: Towards fast and scalable solutions for fMRI big data analytics. BigData 2016: 3396-3403 - [c156]Yan Li, Lu Wang, Jie Wang, Jieping Ye, Chandan K. Reddy:
Transfer Learning for Survival Analysis via Efficient L2, 1-Norm Regularized Cox Regression. ICDM 2016: 231-240 - [c155]Bashar Haddad, Lina J. Karam, Jieping Ye, Nital Patel, Martin Braun:
Multi-feature sparse-based defect detection and classification in semiconductor units. ICIP 2016: 754-758 - [c154]Syed Abbas Z. Naqvi, Shandian Zhe, Yuan Qi, Yifan Yang, Jieping Ye:
Fast Laplace Approximation for Sparse Bayesian Spike and Slab Models. IJCAI 2016: 1867-1973 - [c153]Xiang Li, Binbin Lin, Jinglei Lv, Jieping Ye, Tianming Liu:
Modeling functional network dynamics via multi-scale dictionary learning and network continuums. ISBI 2016: 66-69 - [c152]Jie Zhang, Cynthia M. Stonnington, Qingyang Li, Jie Shi, Robert J. Bauer, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Paul M. Thompson, Jieping Ye, Yalin Wang:
Applying sparse coding to surface multivariate tensor-based morphometry to predict future cognitive decline. ISBI 2016: 646-650 - [c151]Xiang Li, Milad Makkie, Binbin Lin, Mojtaba Sedigh Fazli, Ian Davidson, Jieping Ye, Tianming Liu, Shannon Quinn:
Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis. KDD 2016: 511-519 - [c150]Kai Zhang, Shandian Zhe, Chaoran Cheng, Zhi Wei, Zhengzhang Chen, Haifeng Chen, Guofei Jiang, Yuan Qi, Jieping Ye:
Annealed Sparsity via Adaptive and Dynamic Shrinking. KDD 2016: 1325-1334 - [c149]Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang:
Parallel Lasso Screening for Big Data Optimization. KDD 2016: 1705-1714 - [c148]Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy:
A Multi-Task Learning Formulation for Survival Analysis. KDD 2016: 1715-1724 - [c147]Zhi Nie, Pinghua Gong, Jieping Ye:
Predict Risk of Relapse for Patients with Multiple Stages of Treatment of Depression. KDD 2016: 1795-1804 - [c146]Tao Yang, Jun Liu, Pinghua Gong, Ruiwen Zhang, Xiaotong Shen, Jieping Ye:
Absolute Fused Lasso and Its Application to Genome-Wide Association Studies. KDD 2016: 1955-1964 - [c145]Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Hierarchical Incomplete Multi-source Feature Learning for Spatiotemporal Event Forecasting. KDD 2016: 2085-2094 - [c144]Jie Zhang, Jie Shi, Cynthia M. Stonnington, Qingyang Li, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Hyperbolic Space Sparse Coding with Its Application on Prediction of Alzheimer's Disease in Mild Cognitive Impairment. MICCAI (1) 2016: 326-334 - [c143]Qingyang Li, Tao Yang, Liang Zhan, Derrek P. Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang:
Large-Scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions. MICCAI (1) 2016: 335-343 - [c142]Dajiang Zhu, Binbin Lin, Joshua Faskowitz, Jieping Ye, Paul M. Thompson:
Embedded sparse representation of fMRI data via group-wise dictionary optimization. Medical Imaging: Image Processing 2016: 97841K - [c141]
- [i25]Weizhong Zhang, Bin Hong, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang:
Scaling Up Sparse Support Vector Machine by Simultaneous Feature and Sample Reduction. CoRR abs/1607.06996 (2016) - [i24]Kai Zhang, Chuanren Liu, Jie Zhang, Hui Xiong, Eric P. Xing, Jieping Ye:
Seeing the Forest from the Trees in Two Looks: Matrix Sketching by Cascaded Bilateral Sampling. CoRR abs/1607.07395 (2016) - [i23]Ming Lin, Jieping Ye:
A Non-convex One-Pass Framework for Generalized Factorization Machines and Rank-One Matrix Sensing. CoRR abs/1608.05995 (2016) - [i22]Qingyang Li, Tao Yang, Liang Zhan, Derrek P. Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang:
Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions. CoRR abs/1608.07251 (2016) - 2015
- [j76]Shuo Xiang, Xiaotong Shen, Jieping Ye:
Efficient nonconvex sparse group feature selection via continuous and discrete optimization. Artif. Intell. 224: 28-50 (2015) - [j75]Tao Zeng, Rongjian Li, Ravi Mukkamala, Jieping Ye, Shuiwang Ji:
Deep convolutional neural networks for annotating gene expression patterns in the mouse brain. BMC Bioinformatics 16: 147:1-147:10 (2015) - [j74]Deepak Kadetotad, Zihan Xu, Abinash Mohanty, Pai-Yu Chen, Binbin Lin, Jieping Ye, Sarma B. K. Vrudhula, Shimeng Yu, Yu Cao, Jae-sun Seo:
Parallel Architecture With Resistive Crosspoint Array for Dictionary Learning Acceleration. IEEE J. Emerg. Sel. Topics Circuits Syst. 5(2): 194-204 (2015) - [j73]Qi Yan, Jieping Ye, Xiaotong Shen:
Simultaneous pursuit of sparseness and rank structures for matrix decomposition. Journal of Machine Learning Research 16: 47-75 (2015) - [j72]Jie Wang, Peter Wonka, Jieping Ye:
Lasso screening rules via dual polytope projection. Journal of Machine Learning Research 16: 1063-1101 (2015) - [j71]Jie Wang, Wei Fan, Jieping Ye:
Fused Lasso Screening Rules via the Monotonicity of Subdifferentials. IEEE Trans. Pattern Anal. Mach. Intell. 37(9): 1806-1820 (2015) - [j70]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Qian Sun, Sethuraman Panchanathan, Jieping Ye:
Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds. IEEE Trans. Pattern Anal. Mach. Intell. 37(10): 1945-1958 (2015) - [j69]Sen Yang, Zhaosong Lu, Xiaotong Shen, Peter Wonka, Jieping Ye:
Fused Multiple Graphical Lasso. SIAM Journal on Optimization 25(2): 916-943 (2015) - [j68]Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye:
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion. SIAM J. Scientific Computing 37(1) (2015) - [j67]Jinglei Lv, Xi Jiang, Xiang Li, Dajiang Zhu, Shu Zhang, Shijie Zhao, Hanbo Chen, Tuo Zhang, Xintao Hu, Junwei Han, Jieping Ye, Lei Guo, Tianming Liu:
Holistic Atlases of Functional Networks and Interactions Reveal Reciprocal Organizational Architecture of Cortical Function. IEEE Trans. Biomed. Engineering 62(4): 1120-1131 (2015) - [j66]Zheng Wang, Jieping Ye:
Querying Discriminative and Representative Samples for Batch Mode Active Learning. TKDD 9(3): 17:1-17:23 (2015) - [j65]Buyue Qian, Xiang Wang, Jieping Ye, Ian Davidson:
A Reconstruction Error Based Framework for Multi-Label and Multi-View Learning. IEEE Trans. Knowl. Data Eng. 27(3): 594-607 (2015) - [j64]Moo K. Chung, Jamie L. Hanson, Jieping Ye, Richard J. Davidson, Seth D. Pollak:
Persistent Homology in Sparse Regression and Its Application to Brain Morphometry. IEEE Trans. Med. Imaging 34(9): 1928-1939 (2015) - [c140]Pai-Yu Chen, Deepak Kadetotad, Zihan Xu, Abinash Mohanty, Binbin Lin, Jieping Ye, Sarma B. K. Vrudhula, Jae-sun Seo, Yu Cao, Shimeng Yu:
Technology-design co-optimization of resistive cross-point array for accelerating learning algorithms on chip. DATE 2015: 854-859 - [c139]Pai-Yu Chen, Binbin Lin, I-Ting Wang, Tuo-Hung Hou, Jieping Ye, Sarma B. K. Vrudhula, Jae-sun Seo, Yu Cao, Shimeng Yu:
Mitigating Effects of Non-ideal Synaptic Device Characteristics for On-chip Learning. ICCAD 2015: 194-199 - [c138]Hemanth Venkateswara, Prasanth Lade, Binbin Lin, Jieping Ye, Sethuraman Panchanathan:
Efficient Approximate Solutions to Mutual Information Based Global Feature Selection. ICDM 2015: 1009-1014 - [c137]Pinghua Gong, Jieping Ye:
A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence Analysis. ICML 2015: 276-284 - [c136]
- [c135]Liang Zhan, Yashu Liu, Jiayu Zhou, Jieping Ye, Paul M. Thompson:
Boosting classification accuracy of diffusion MRI derived brain networks for the subtypes of mild cognitive impairment using higher order singular value decomposition. ISBI 2015: 131-135 - [c134]Tao Yang, Jie Wang, Qian Sun, Derrek P. Hibar, Neda Jahanshad, Li Liu, Yalin Wang, Liang Zhan, Paul M. Thompson, Jieping Ye:
Detecting genetic risk factors for Alzheimer's disease in whole genome sequence data via Lasso screening. ISBI 2015: 985-989 - [c133]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Adepu Ravi Sankar, Sethuraman Panchanathan, Jieping Ye:
BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification. KDD 2015: 99-108 - [c132]Chia-Tung Kuo, Xiang Wang, Peter B. Walker, Owen T. Carmichael, Jieping Ye, Ian Davidson:
Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation. KDD 2015: 617-626 - [c131]Zheng Wang, Prithwish Chakraborty, Sumiko R. Mekaru, John S. Brownstein, Jieping Ye, Naren Ramakrishnan:
Dynamic Poisson Autoregression for Influenza-Like-Illness Case Count Prediction. KDD 2015: 1285-1294 - [c130]Sen Yang, Qian Sun, Shuiwang Ji, Peter Wonka, Ian Davidson, Jieping Ye:
Structural Graphical Lasso for Learning Mouse Brain Connectivity. KDD 2015: 1385-1394 - [c129]Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, Shuiwang Ji:
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis. KDD 2015: 1475-1484 - [c128]Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Multi-Task Learning for Spatio-Temporal Event Forecasting. KDD 2015: 1503-1512 - [c127]Qian Sun, Mohammad Shafkat Amin, Baoshi Yan, Craig Martell, Vita Markman, Anmol Bhasin, Jieping Ye:
Transfer Learning for Bilingual Content Classification. KDD 2015: 2147-2156 - [c126]Jinglei Lv, Binbin Lin, Wei Zhang, Xi Jiang, Xintao Hu, Junwei Han, Lei Guo, Jieping Ye, Tianming Liu:
Modeling Task FMRI Data via Supervised Stochastic Coordinate Coding. MICCAI (1) 2015: 239-246 - [c125]Hemanth Venkateswara, Prasanth Lade, Jieping Ye, Sethuraman Panchanathan:
Coupled Support Vector Machines for Supervised Domain Adaptation. ACM Multimedia 2015: 1295-1298 - [c124]Somak Aditya, Chitta Baral, Nguyen Ha Vo, Joohyung Lee, Jieping Ye, Zaw Naung, Barry Lumpkin, Jenny Hastings, Richard B. Scherl, Dawn M. Sweet, Daniela Inclezan:
Recognizing Social Constructs from Textual Conversation. HLT-NAACL 2015: 1293-1298 - [c123]Pinghua Gong, Jieping Ye:
HONOR: Hybrid Optimization for NOn-convex Regularized problems. NIPS 2015: 415-423 - [c122]
- [c121]Graciela Gonzalez, Chitta Baral, Jeff Kiefer, Suengchan Kim, Jieping Ye:
Session Introduction. Pacific Symposium on Biocomputing 2015: 80-83 - [c120]Tao Yang, Xinlin Zhao, Binbin Lin, Tao Zeng, Shuiwang Ji, Jieping Ye:
Automated Gene Expression Pattern Annotation in the Mouse Brain. Pacific Symposium on Biocomputing 2015: 144-155 - [c119]