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2020 – today
- 2020
[j98]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. IEEE Trans. Big Data 6(2): 322-333 (2020)- [c212]Mengyue Yang, Qingyang Li, Zhiwei Qin, Jieping Ye:
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. WWW 2020: 292-302 - [i67]Jie Gui, Zhenan Sun, Yonggang Wen, Dacheng Tao, Jieping Ye:
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications. CoRR abs/2001.06937 (2020) - [i66]Chengchun Shi, Xiaoyu Wang, Shikai Luo, Rui Song, Hongtu Zhu, Jieping Ye:
A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing. CoRR abs/2002.01711 (2020) - [i65]Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
Upper Confidence Primal-Dual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions. CoRR abs/2003.00660 (2020) - [i64]Luanxuan Hou, Jie Cao, Yuan Zhao, Haifeng Shen, Yiping Meng, Ran He, Jieping Ye:
Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation. CoRR abs/2003.07516 (2020) - [i63]Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye:
Adaptive Object Detection with Dual Multi-Label Prediction. CoRR abs/2003.12943 (2020) - [i62]Zhenpeng Li, Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye:
Mutual Learning Network for Multi-Source Domain Adaptation. CoRR abs/2003.12944 (2020) - [i61]Mengyue Yang, Qingyang Li, Zhiwei Qin, Jieping Ye:
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. CoRR abs/2004.01136 (2020) - [i60]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting. CoRR abs/2004.10958 (2020) - [i59]Chao Xiong, Che Liu, Zijun Xu, Junfeng Jiang, Jieping Ye:
Sequential Sentence Matching Network for Multi-turn Response Selection in Retrieval-based Chatbots. CoRR abs/2005.07923 (2020) - [i58]Bingyu Liu, Zhen Zhao, Zhenpeng Li, Jianan Jiang, Yuhong Guo, Jieping Ye:
Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification. CoRR abs/2005.08463 (2020)
2010 – 2019
- 2019
- [j97]Yan Li, Lu Wang, Jiayu Zhou
, Jieping Ye:
Multi-task learning based survival analysis for multi-source block-wise missing data. Neurocomputing 364: 95-107 (2019) - [j96]Milad Makkie, Xiang Li, Shannon Quinn, Binbin Lin, Jieping Ye, Geoffrey Mon, Tianming Liu:
A Distributed Computing Platform for fMRI Big Data Analytics. IEEE Trans. Big Data 5(2): 109-119 (2019) - [j95]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) - [j94]Kefei Liu, Jieping Ye, Yang Yang, Li Shen, Hui Jiang:
A Unified Model for Joint Normalization and Differential Gene Expression Detection in RNA-Seq Data. IEEE/ACM Trans. Comput. Biology Bioinform. 16(2): 442-454 (2019) - [j93]Jintao Ke, Hai Yang, Hongyu Zheng, Xiqun Chen, Yitian Jia, Pinghua Gong, Jieping Ye:
Hexagon-Based Convolutional Neural Network for Supply-Demand Forecasting of Ride-Sourcing Services. IEEE Trans. Intell. Transp. Syst. 20(11): 4160-4173 (2019) - [c211]Ji Zhao, Dan Peng, Chuhan Wu, Huan Chen, Meiyu Yu, Wanji Zheng, Li Ma, Hua Chai, Jieping Ye, Xiaohu Qie:
Incorporating Semantic Similarity with Geographic Correlation for Query-POI Relevance Learning. AAAI 2019: 1270-1277 - [c210]Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, Yan Liu:
Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting. AAAI 2019: 3656-3663 - [c209]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. AAAI 2019: 4312-4319 - [c208]Tao Huang, Yintai Ma, Zhiwei (Tony) Qin, Jianfeng Zheng, Henry X. Liu, Hongtu Zhu, Jieping Ye:
Origin-destination Flow Prediction with Vehicle Trajectory Data and Semi-supervised Recurrent Neural Network. BigData 2019: 1450-1459 - [c207]Lingyu Zhang, Tianshu Song, Yongxin Tong, Zimu Zhou, Dan Li, Wei Ai, Lulu Zhang, Guobin Wu, Yan Liu, Jieping Ye:
Recommendation-based Team Formation for On-demand Taxi-calling Platforms. CIKM 2019: 59-68 - [c206]Jiarui Jin, Ming Zhou, Weinan Zhang, Minne Li, Zilong Guo, Zhiwei Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, Jieping Ye:
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms. CIKM 2019: 1983-1992 - [c205]Ming Zhou, Jiarui Jin, Weinan Zhang, Zhiwei Qin, Yan Jiao, Chenxi Wang, Guobin Wu, Yong Yu, Jieping Ye:
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching. CIKM 2019: 2645-2653 - [c204]Weinan Zhang, Haiming Jin, Lingyu Zhang, Hongtu Zhu, Zhenhui Jessie Li, Jieping Ye:
CIKM 2019 Workshop on Artificial Intelligence in Transportation (AI in transportation). CIKM 2019: 2995-2996 - [c203]Zhengxia Zou, Wenyuan Li, Tianyang Shi, Zhenwei Shi, Jieping Ye:
Generative Adversarial Training for Weakly Supervised Cloud Matting. ICCV 2019: 201-210 - [c202]Max Guangyu Li, Bo Jiang, Zhengping Che, Xuefeng Shi, Mengyao Liu, Yiping Meng, Jieping Ye, Yan Liu:
DBUS: Human Driving Behavior Understanding System. ICCV Workshops 2019: 2436-2444 - [c201]Peng Cheng, Lei Chen, Jieping Ye:
Cooperation-Aware Task Assignment in Spatial Crowdsourcing. ICDE 2019: 1442-1453 - [c200]Haipeng Chen, Yan Jiao, Zhiwei Qin, Xiaocheng Tang, Hao Li, Bo An, Hongtu Zhu, Jieping Ye:
InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms. ICDM 2019: 61-70 - [c199]John Holler, Risto Vuorio, Zhiwei Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye:
Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem. ICDM 2019: 1090-1095 - [c198]Qunxi Dong, Jie Zhang, Qingyang Li, Paul M. Thompson, Richard J. Caselli, Jieping Ye, Yalin Wang:
Multi-task Dictionary Learning Based on Convolutional Neural Networks for Longitudinal Clinical Score Predictions in Alzheimer's Disease. HBAI@IJCAI 2019: 21-35 - [c197]Pei Yang, Qi Tan, Jieping Ye, Hanghang Tong, Jingrui He:
Deep Multi-Task Learning with Adversarial-and-Cooperative Nets. IJCAI 2019: 4078-4084 - [c196]Jun Chen, Ji Zhu, Jieping Ye:
An Attention-Based Hybrid Network for Automatic Detection of Alzheimer's Disease from Narrative Speech. INTERSPEECH 2019: 4085-4089 - [c195]Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei Qin, Yiping Meng, Jieping Ye:
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation. KDD 2019: 566-576 - [c194]Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye:
A Deep Value-network Based Approach for Multi-Driver Order Dispatching. KDD 2019: 1780-1790 - [c193]Chunyi Liu, Peng Wang, Jiang Xu, Zang Li, Jieping Ye:
Automatic Dialogue Summary Generation for Customer Service. KDD 2019: 1957-1965 - [c192]Jieping Ye:
Transportation: A Data Driven Approach. KDD 2019: 3183 - [c191]Zhiwei (Tony) Qin, Jian Tang, Jieping Ye:
Deep Reinforcement Learning with Applications in Transportation. KDD 2019: 3201-3202 - [c190]Fan Zhou, Tengfei Li, Haibo Zhou, Hongtu Zhu, Jieping Ye:
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response. NeurIPS 2019: 7013-7023 - [c189]Minne Li, Zhiwei Qin, Yan Jiao, Yaodong Yang, Jun Wang, Chenxi Wang, Guobin Wu, Jieping Ye:
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning. WWW 2019: 983-994 - [i57]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) - [i56]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) - [i55]Jintao Ke, Feng Xiao, Hai Yang, Jieping Ye:
Optimizing Online Matching for Ride-Sourcing Services with Multi-Agent Deep Reinforcement Learning. CoRR abs/1902.06228 (2019) - [i54]Ji Zhao, Meiyu Yu, Huan Chen, Boning Li, Lingyu Zhang, Qi Song, Li Ma, Hua Chai, Jieping Ye:
POI Semantic Model with a Deep Convolutional Structure. CoRR abs/1903.07279 (2019) - [i53]Zhengping Che, Max Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, Jieping Ye:
D2-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios. CoRR abs/1904.01975 (2019) - [i52]Zhengxia Zou, Zhenwei Shi, Yuhong Guo, Jieping Ye:
Object Detection in 20 Years: A Survey. CoRR abs/1905.05055 (2019) - [i51]Zhenyu Shou, Xuan Di, Jieping Ye, Hongtu Zhu, Robert C. Hampshire:
Where to Find Next Passengers on E-hailing Platforms? - A Markov Decision Process Approach. CoRR abs/1905.09906 (2019) - [i50]Jiarui Jin, Ming Zhou, Weinan Zhang, Minne Li, Zilong Guo, Zhiwei Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, Jieping Ye:
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms. CoRR abs/1905.11353 (2019) - [i49]Xu Geng, Xiyu Wu, Lingyu Zhang, Qiang Yang, Yan Liu, Jieping Ye:
Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting. CoRR abs/1905.11395 (2019) - [i48]Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang, Jieping Ye:
AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates. CoRR abs/1907.03141 (2019) - [i47]Guojun Wu, Yanhua Li, Zhenming Liu, Jie Bao, Yu Zheng, Jieping Ye, Jun Luo:
Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle. CoRR abs/1907.05390 (2019) - [i46]Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei Qin, Yiping Meng, Jieping Ye:
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation. CoRR abs/1907.06584 (2019) - [i45]Yucheng Lin, Xiaoqing Yang, Zang Li, Jieping Ye:
AHINE: Adaptive Heterogeneous Information Network Embedding. CoRR abs/1909.01087 (2019) - [i44]Huapeng Wu, Zhengxia Zou, Jie Gui, Wen-Jun Zeng, Jieping Ye, Jun Zhang, Hongyi Liu, Zhihui Wei:
Multi-grained Attention Networks for Single Image Super-Resolution. CoRR abs/1909.11937 (2019) - [i43]Shupeng Gui, Xiangliang Zhang, Pan Zhong, Shuang Qiu, Mingrui Wu, Jieping Ye, Zhengdao Wang, Ji Liu:
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions. CoRR abs/1909.12903 (2019) - [i42]Ming Zhou, Jiarui Jin, Weinan Zhang, Zhiwei Qin, Yan Jiao, Chenxi Wang, Guobin Wu, Yong Yu, Jieping Ye:
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching. CoRR abs/1910.02591 (2019) - [i41]Jintao Ke, Xiaoran Qin, Hai Yang, Zhengfei Zheng, Zheng Zhu, Jieping Ye:
Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network. CoRR abs/1910.09103 (2019) - [i40]Yang Liu, Fanyou Wu, Baosheng Yu, Zhiyuan Liu, Jieping Ye:
Building Effective Large-Scale Traffic State Prediction System: Traffic4cast Challenge Solution. CoRR abs/1911.05699 (2019) - [i39]John Holler, Risto Vuorio, Zhiwei Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye:
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem. CoRR abs/1911.11260 (2019) - [i38]Huiting Hong, Hantao Guo, Yucheng Lin, Xiaoqing Yang, Zang Li, Jieping Ye:
An Attention-based Graph Neural Network for Heterogeneous Structural Learning. CoRR abs/1912.10832 (2019) - 2018
- [j92]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) - [j91]Libin Zheng, Lei Chen, Jieping Ye:
Order Dispatch in Price-aware Ridesharing. Proc. VLDB Endow. 11(8): 853-865 (2018) - [j90]Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Jieping Ye, Ke Xu:
A Unified Approach to Route Planning for Shared Mobility. Proc. VLDB Endow. 11(11): 1633-1646 (2018) - [j89]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 Autom. Sci. Eng. 15(1): 145-159 (2018) - [j88]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) - [j87]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]Guojun Wu, Yanhua Li, Jie Bao, Yu Zheng, Jieping Ye, Jun Luo:
Human-Centric Urban Transit Evaluation and Planning. ICDM 2018: 547-556 - [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]Zheng Wang, Kun Fu, Jieping Ye:
Learning to Estimate the Travel Time. KDD 2018: 858-866 - [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]Yan Li, Jieping Ye:
Learning Adversarial Networks for Semi-Supervised Text Classification via Policy Gradient. KDD 2018: 1715-1723 - [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]Jieping Ye:
Big Data at Didi Chuxing. SIGIR 2018: 1341 - [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
- [j86]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 Anal. 38: 1-16 (2017) - [j85]Yongxin Tong, Libin Wang, Zimu Zhou, Bolin Ding, Lei Chen, Jieping Ye, Ke Xu:
Flexible Online Task Assignment in Real-Time Spatial Data. Proc. VLDB Endow. 10(11): 1334-1345 (2017) - [j84]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]Dong Wang, Wei Cao, Jian Li, Jieping Ye:
DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks. ICDE 2017: 243-254 - [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
- [j83]Kefei Liu, Lei Huang, Hing-Cheung So, Jieping Ye:
Multidimensional folding for sinusoidal order selection. Digit. Signal Process. 48: 349-360 (2016) - [j82]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. Digit. Signal Process. 51: 110-123 (2016) - [j81]Zhenfeng Zhu, Jian Cheng, Yao Zhao, Jieping Ye:
LSSLP - Local structure sensitive label propagation. Inf. Sci. 332: 19-32 (2016) - [j80]