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2020 – today
- 2022
[j123]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. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 770-782 (2022)- [j122]Yuan Cao, Junwei Liu, Heng Qi, Jie Gui, Keqiu Li, Jieping Ye, Chao Liu:
Scalable Distributed Hashing for Approximate Nearest Neighbor Search. IEEE Trans. Image Process. 31: 472-484 (2022) - [j121]Yiwen Sun, Kun Fu, Zheng Wang, Donghua Zhou, Kailun Wu, Jieping Ye, Changshui Zhang:
CoDriver ETA: Combine Driver Information in Estimated Time of Arrival by Driving Style Learning Auxiliary Task. IEEE Trans. Intell. Transp. Syst. 23(5): 4037-4048 (2022) - [j120]Siyuan Feng, Jintao Ke, Hai Yang, Jieping Ye:
A Multi-Task Matrix Factorized Graph Neural Network for Co-Prediction of Zone-Based and OD-Based Ride-Hailing Demand. IEEE Trans. Intell. Transp. Syst. 23(6): 5704-5716 (2022) - [j119]Guangtao Wang, Gao Cong, Ying Zhang, Zhen Hai, Jieping Ye:
A Synopsis Based Approach for Itemset Frequency Estimation over Massive Multi-Transaction Stream. ACM Trans. Knowl. Discov. Data 16(2): 29:1-29:30 (2022) - [j118]Liang Zhao, Yuyang Gao, Jieping Ye, Feng Chen, Yanfang Ye, Chang-Tien Lu, Naren Ramakrishnan:
Spatio-Temporal Event Forecasting Using Incremental Multi-Source Feature Learning. ACM Trans. Knowl. Discov. Data 16(2): 40:1-40:28 (2022) - [j117]Jintao Ke, Feng Xiao, Hai Yang, Jieping Ye:
Learning to Delay in Ride-Sourcing Systems: A Multi-Agent Deep Reinforcement Learning Framework. IEEE Trans. Knowl. Data Eng. 34(5): 2280-2292 (2022) - [j116]Xuanzhao Wang, Zhengping Che, Bo Jiang, Ning Xiao, Ke Yang, Jian Tang, Jieping Ye, Jingyu Wang, Qi Qi:
Robust Unsupervised Video Anomaly Detection by Multipath Frame Prediction. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2301-2312 (2022) - [c249]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference 2022: 1286-1300 - [c248]Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu:
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. WWW 2022: 798-807 - [i96]Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu:
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. CoRR abs/2202.05679 (2022) - [i95]Shikai Luo, Ying Yang, Chengchun Shi, Fang Yao, Jieping Ye, Hongtu Zhu:
Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms. CoRR abs/2202.10887 (2022) - [i94]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic Gradient Descent without Full Data Shuffle. CoRR abs/2206.05830 (2022) - [i93]Langzhang Liang, Zenglin Xu, Zixing Song, Irwin King, Jieping Ye:
ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization. CoRR abs/2206.08181 (2022) - [i92]Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions. CoRR abs/2207.12463 (2022) - 2021
- [j115]Shuang Qiu, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
On Finite-Time Convergence of Actor-Critic Algorithm. IEEE J. Sel. Areas Inf. Theory 2(2): 652-664 (2021) - [j114]Jie Zhang, Qunxi Dong, Jie Shi, Qingyang Li, Cynthia M. Stonnington, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Predicting future cognitive decline with hyperbolic stochastic coding. Medical Image Anal. 70: 102009 (2021) - [j113]Wenjie Shang, Qingyang Li, Zhiwei (Tony) Qin, Yang Yu, Yiping Meng, Jieping Ye:
Partially observable environment estimation with uplift inference for reinforcement learning based recommendation. Mach. Learn. 110(9): 2603-2640 (2021) - [j112]Lina J. Karam, Jay Katupitiya, Vicente Milanés, Ioannis Pitas, Jieping Ye:
Autonomous Driving: Part 2-Learning and Cognition [From the Guest Editors]. IEEE Signal Process. Mag. 38(1): 20-21 (2021) - [j111]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. IEEE Trans. Circuits Syst. Video Technol. 31(2): 512-522 (2021) - [j110]Zhiyuan Liu, Yang Liu, Cheng Lyu, Jieping Ye:
Building Personalized Transportation Model for Online Taxi-Hailing Demand Prediction. IEEE Trans. Cybern. 51(9): 4602-4610 (2021) - [j109]Zhengxia Zou, Tianyang Shi, Zhenwei Shi, Jieping Ye:
Adversarial Training for Solving Inverse Problems in Image Processing. IEEE Trans. Image Process. 30: 2513-2525 (2021) - [j108]Jie Gui, Yuan Cao, Heng Qi, Keqiu Li, Jieping Ye, Chao Liu, Xiaowei Xu:
Fast kNN Search in Weighted Hamming Space With Multiple Tables. IEEE Trans. Image Process. 30: 3985-3994 (2021) - [j107]Rui Han, Chi Harold Liu, Shilin Li, Lydia Y. Chen, Guoren Wang, Jian Tang, Jieping Ye:
SlimML: Removing Non-Critical Input Data in Large-Scale Iterative Machine Learning. IEEE Trans. Knowl. Data Eng. 33(5): 2223-2236 (2021) - [j106]Jie Zhang, Jianfeng Wu, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Multi-Resemblance Multi-Target Low-Rank Coding for Prediction of Cognitive Decline With Longitudinal Brain Images. IEEE Trans. Medical Imaging 40(8): 2030-2041 (2021) - [j105]Zhengtian Xu, Zhibin Chen, Yafeng Yin, Jieping Ye:
Equilibrium Analysis of Urban Traffic Networks with Ride-Sourcing Services. Transp. Sci. 55(6): 1260-1279 (2021) - [c247]Bingyu Liu, Yuhong Guo, Jieping Ye, Weihong Deng:
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation. BMVC 2021: 299 - [c246]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Ziang Yan, Changshui Zhang, Jieping Ye:
FMA-ETA: Estimating Travel Time Entirely Based on FFN with Attention. ICASSP 2021: 3355-3359 - [c245]Fan Zhou, Chenfan Lu, Xiaocheng Tang, Fan Zhang, Zhiwei Qin, Jieping Ye, Hongtu Zhu:
Multi-Objective Distributional Reinforcement Learning for Large-Scale Order Dispatching. ICDM 2021: 1541-1546 - [c244]Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions. ICML 2021: 8715-8725 - [c243]Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game. ICML 2021: 8737-8747 - [c242]Jun Chen, Jieping Ye, Fengyi Tang, Jiayu Zhou:
Automatic Detection of Alzheimer's Disease Using Spontaneous Speech Only. Interspeech 2021: 3830-3834 - [c241]Zhiwei (Tony) Qin, Hongtu Zhu, Jieping Ye:
Reinforcement Learning for Ridesharing: A Survey. ITSC 2021: 2447-2454 - [c240]Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. KDD 2021: 3605-3615 - [c239]Jian Zhang, Jian Tang, Yiran Chen, Jie Liu, Jieping Ye, Marilyn Wolf, Vijaykrishnan Narayanan, Mani Srivastava, Michael I. Jordan, Victor Bahl:
The 4th Artificial Intelligence of Things (AIoT) Workshop. KDD 2021: 4179-4180 - [c238]Xun Zhou, Liang Zhao, Zhe Jiang, Robert N. Stewart, Shashi Shekhar, Jieping Ye:
DeepSpatial'21: 2nd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems. KDD 2021: 4183-4184 - [c237]Xiong-Hui Chen, Yang Yu, Qingyang Li, Fan-Ming Luo, Zhiwei (Tony) Qin, Wenjie Shang, Jieping Ye:
Offline Model-based Adaptable Policy Learning. NeurIPS 2021: 8432-8443 - [i91]Jie Zhang, Qunxi Dong, Jie Shi, Qingyang Li, Cynthia M. Stonnington, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Predicting Future Cognitive Decline with Hyperbolic Stochastic Coding. CoRR abs/2102.10503 (2021) - [i90]Yan Jiao, Xiaocheng Tang, Zhiwei (Tony) Qin, Shuaiji Li, Fan Zhang, Hongtu Zhu, Jieping Ye:
Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning. CoRR abs/2103.04555 (2021) - [i89]Zhiwei (Tony) Qin, Hongtu Zhu, Jieping Ye:
Reinforcement Learning for Ridesharing: A Survey. CoRR abs/2105.01099 (2021) - [i88]Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. CoRR abs/2105.08791 (2021) - [i87]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. CoRR abs/2106.04493 (2021) - [i86]Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game. CoRR abs/2110.09771 (2021) - 2020
- [j104]Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Fan Zhang, Zhe Xu, Hongtu Zhu, Jieping Ye:
Ride-Hailing Order Dispatching at DiDi via Reinforcement Learning. INFORMS J. Appl. Anal. 50(5): 272-286 (2020) - [j103]Lina J. Karam, Jay Katupitiya, Vicente Milanés, Ioannis Pitas, Jieping Ye:
Autonomous Driving: Part 1-Sensing and Perception [From the Guest Editors]. IEEE Signal Process. Mag. 37(4): 11-13 (2020) - [j102]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) - [j101]Yang Liu, Zhiyuan Liu, Cheng Lyu, Jieping Ye:
Attention-Based Deep Ensemble Net for Large-Scale Online Taxi-Hailing Demand Prediction. IEEE Trans. Intell. Transp. Syst. 21(11): 4798-4807 (2020) - [c236]Huiting Hong, Hantao Guo, Yucheng Lin, Xiaoqing Yang, Zang Li, Jieping Ye:
An Attention-Based Graph Neural Network for Heterogeneous Structural Learning. AAAI 2020: 4132-4139 - [c235]Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang, Jieping Ye:
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates. AAAI 2020: 4876-4883 - [c234]Peng Wang, Jiang Xu, Chunyi Liu, Hao Feng, Zang Li, Jieping Ye:
Masked-field Pre-training for User Intent Prediction. CIKM 2020: 2789-2796 - [c233]Guojun Wu, Yanhua Li, Shikai Luo, Ge Song, Qichao Wang, Jing He, Jieping Ye, Xiaohu Qie, Hongtu Zhu:
A Joint Inverse Reinforcement Learning and Deep Learning Model for Drivers' Behavioral Prediction. CIKM 2020: 2805-2812 - [c232]Xiehe Huang, Weihong Deng, Haifeng Shen, Xiubao Zhang, Jieping Ye:
PropagationNet: Propagate Points to Curve to Learn Structure Information. CVPR 2020: 7263-7272 - [c231]Zhengxia Zou, Sen Lei, Tianyang Shi, Zhenwei Shi, Jieping Ye:
Deep Adversarial Decomposition: A Unified Framework for Separating Superimposed Images. CVPR 2020: 12803-12813 - [c230]Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye:
Adaptive Object Detection with Dual Multi-label Prediction. ECCV (28) 2020: 54-69 - [c229]Zhen Zhao, Yuhong Guo, Jieping Ye:
Bi-Dimensional Feature Alignment for Cross-Domain Object Detection. ECCV Workshops (1) 2020: 671-686 - [c228]Yucheng Lin, Huiting Hong, Xiaoqing Yang, Pinghua Gong, Zang Li, Jieping Ye:
AHINE: Adaptive Heterogeneous Information Network Embedding. ICKG 2020: 100-107 - [c227]Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu:
Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network. ICDE 2020: 1818-1821 - [c226]Yuan Zhao, Lyuwei Wang, Luanxuan Hou, Chunsheng Gan, Zhipeng Huang, Xu Hu, Haifeng Shen, Jieping Ye:
Real Time Object Detection for Traffic Based on Knowledge Distillation: 3rd Place Solution to Pair Competition. ICME Workshops 2020: 1-6 - [c225]Zehui Yu, Xiehe Huang, Xiubao Zhang, Haifeng Shen, Qun Li, Weihong Deng, Jian Tang, Yi Yang, Jieping Ye:
A Multi-Modal Approach for Driver Gaze Prediction to Remove Identity Bias. ICMI 2020: 768-776 - [c224]Mo Sun, Jian Li, Hui Feng, Wei Gou, Haifeng Shen, Jian Tang, Yi Yang, Jieping Ye:
Multi-modal Fusion Using Spatio-temporal and Static Features for Group Emotion Recognition. ICMI 2020: 835-840 - [c223]Yiwen Sun, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Road Network Metric Learning for Estimated Time of Arrival. ICPR 2020: 1820-1827 - [c222]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting. ICPR 2020: 3483-3490 - [c221]Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, Qiaozhu Mei:
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy. KDD 2020: 2368-2377 - [c220]Huiting Hong, Yucheng Lin, Xiaoqing Yang, Zang Li, Kun Fu, Zheng Wang, Xiaohu Qie, Jieping Ye:
HetETA: Heterogeneous Information Network Embedding for Estimating Time of Arrival. KDD 2020: 2444-2454 - [c219]Wenjuan Luo, Han Zhang, Xiaodi Yang, Lin Bo, Xiaoqing Yang, Zang Li, Xiaohu Qie, Jieping Ye:
Dynamic Heterogeneous Graph Neural Network for Real-time Event Prediction. KDD 2020: 3213-3223 - [c218]Kun Fu, Fanlin Meng, Jieping Ye, Zheng Wang:
CompactETA: A Fast Inference System for Travel Time Prediction. KDD 2020: 3337-3345 - [c217]Che Liu, Junfeng Jiang, Chao Xiong, Yi Yang, Jieping Ye:
Towards Building an Intelligent Chatbot for Customer Service: Learning to Respond at the Appropriate Time. KDD 2020: 3377-3385 - [c216]Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss. NeurIPS 2020 - [c215]Zhiyuan Xu, Kun Wu, Zhengping Che, Jian Tang, Jieping Ye:
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control. NeurIPS 2020 - [c214]Bo Long, Jieping Ye, Zang Li, Huiji Gao, Sandeep Kumar Jha:
Deep Natural Language Processing for Search and Recommendation. SIGIR 2020: 2461-2463 - [c213]Tanfang Chen, Weiwei Wang, Wenyang Wei, Xing Shi, Xiangang Li, Jieping Ye, Kevin Knight:
DiDi's Machine Translation System for WMT2020. WMT@EMNLP 2020: 105-112 - [c212]Mengyue Yang, Qingyang Li, Zhiwei (Tony) Qin, Jieping Ye:
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. WWW 2020: 292-302 - [i85]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) - [i84]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) - [i83]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) - [i82]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) - [i81]Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye:
Adaptive Object Detection with Dual Multi-Label Prediction. CoRR abs/2003.12943 (2020) - [i80]Zhenpeng Li, Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye:
Mutual Learning Network for Multi-Source Domain Adaptation. CoRR abs/2003.12944 (2020) - [i79]Mengyue Yang, Qingyang Li, Zhiwei (Tony) Qin, Jieping Ye:
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. CoRR abs/2004.01136 (2020) - [i78]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) - [i77]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) - [i76]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) - [i75]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Fusion Recurrent Neural Network. CoRR abs/2006.04069 (2020) - [i74]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Ziang Yan, Changshui Zhang, Jieping Ye:
FMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention. CoRR abs/2006.04077 (2020) - [i73]Zhen Zhao, Bingyu Liu, Yuhong Guo, Jieping Ye:
Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled Data. CoRR abs/2006.04323 (2020) - [i72]Jianan Jiang, Zhenpeng Li, Yuhong Guo, Jieping Ye:
A Transductive Multi-Head Model for Cross-Domain Few-Shot Learning. CoRR abs/2006.11384 (2020) - [i71]Yiwen Sun, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Road Network Metric Learning for Estimated Time of Arrival. CoRR abs/2006.13477 (2020) - [i70]Xiehe Huang, Weihong Deng, Haifeng Shen, Xiubao Zhang, Jieping Ye:
PropagationNet: Propagate Points to Curve to Learn Structure Information. CoRR abs/2006.14308 (2020) - [i69]Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, Qiaozhu Mei:
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy. CoRR abs/2008.07364 (2020) - [i68]Shuang Qiu, Zhuoran Yang, Xiaohan Wei, Jieping Ye, Zhaoran Wang:
Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning. CoRR abs/2008.10103 (2020) - [i67]Jiang Lu, Pinghua Gong, Jieping Ye, Changshui Zhang:
Learning from Very Few Samples: A Survey. CoRR abs/2009.02653 (2020) - [i66]Yucheng Lin, Huiting Hong, Xiaoqing Yang, Xiaodi Yang, Pinghua Gong, Jieping Ye:
Meta Graph Attention on Heterogeneous Graph with Node-Edge Co-evolution. CoRR abs/2010.04554 (2020) - [i65]Zhiyuan Xu, Kun Wu, Zhengping Che, Jian Tang, Jieping Ye:
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control. CoRR abs/2010.07494 (2020) - [i64]Tanfang Chen, Weiwei Wang, Wenyang Wei, Xing Shi, Xiangang Li, Jieping Ye, Kevin Knight:
DiDi's Machine Translation System for WMT2020. CoRR abs/2010.08185 (2020) - [i63]Xuanzhao Wang, Zhengping Che, Ke Yang, Bo Jiang, Jian Tang, Jieping Ye, Jingyu Wang, Qi Qi:
Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction. CoRR abs/2011.02763 (2020) - [i62]Jintao Ke, Siyuan Feng, Zheng Zhu, Hai Yang, Jieping Ye:
Joint predictions of multi-modal ride-hailing demands: a deep multi-task multigraph learning-based approach. CoRR abs/2011.05602 (2020) - [i61]Zhen Zhao, Yuhong Guo, Jieping Ye:
Bi-Dimensional Feature Alignment for Cross-Domain Object Detection. CoRR abs/2011.07205 (2020) - [i60]Zhenpeng Li, Jianan Jiang, Yuhong Guo, Tiantian Tang, Chengxiang Zhuo, Jieping Ye:
Domain Adaptation with Incomplete Target Domains. CoRR abs/2012.01606 (2020) - [i59]Bingyu Liu, Yuhong Guo, Jieping Ye, Weihong Deng:
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation. CoRR abs/2012.03438 (2020) - [i58]Wen-Jun Zeng, Jieping Ye:
Successive Projection for Solving Systems of Nonlinear Equations/Inequalities. CoRR abs/2012.07555 (2020)
2010 – 2019
- 2019
- [j100]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) - [j99]Bin Hong, Weizhong Zhang, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang:
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction. J. Mach. Learn. Res. 20: 121:1-121:39 (2019) - [j98]Jie Wang, Zhanqiu Zhang, Jieping Ye:
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. J. Mach. Learn. Res. 20: 163:1-163:42 (2019) - [j97]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) - [j96]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. Eng. 66(1): 289-299 (2019) - [j95]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. Biol. Bioinform. 16(2): 442-454 (2019) - [j94]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. IEEE 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,