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ORCIDJie Wang 0005
Person information
- affiliation: University of Science and Technology of China (USTC), MIRA Lab, Hefei, China
- affiliation: University of Science and Technology of China, Department of Electronic Engineering and Information Science, Hefei, China
- affiliation: University of Michigan, Ann Arbor, MI, USA
- affiliation (former): Arizona State University, Department of Computer Science and Engineering / Center for Evolutionary Medicine and Informatics of the Biodesign Institute, Tempe, AZ, USA
- affiliation (PhD 2011): Florida State University, Tallahassee, FL, USA
Other persons with the same name
- Jie Wang — disambiguation page
- Jie Wang 0001 — Loughborough University, UK
- Jie Wang 0002
![[0000-0003-1483-2783]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-1483-2783")
— University of Massachusetts Lowell, Department of Computer Science, Lowell, MA, USA - Jie Wang 0003 — Dalian Maritime University, China (and 1 more)
- Jie Wang 0004 — Dalian University of Technology, School of Software Technology, China (and 2 more)
- Jie Wang 0006 — Stanford University, Department of Civil and Environmental Engineering, CA, USA
- Jie Wang 0007 — Chinese Academy of Sciences, Beijing Institute of Nanoenergy and Nanosystems, China (and 2 more)
- Jie Wang 0008 — Indiana University Northwest, Gary, IN, USA (and 3 more)
- Jie Wang 0009 — Hamburg University of Technology, Germany
- Jie Wang 0010 — Epson Edge, Toronto, ON, Canada (and 1 more)
- Jie Wang 0011 — University of Bath, UK (and 1 more)
- Jie Wang 0012 — East China University of Science and Technology, MOE Key Laboratory of Advanced Control and Optimization for Chemical Processes, Shanghai, China
- Jie Wang 0013 — Hangzhou Dianzi University, School of Computer Science and Technology, China
- Jie Wang 0014 — Sichuan Normal University, School of Business, Chengdu, China
- Jie Wang 0015 — Hebei University of Technology, School of Artificial Intelligence, Tianjin, China
- Jie Wang 0016 — North Carolina State University, Department of Electrical and Computer Engineering, Raleigh, NC, USA
- Jie Wang 0017 — China Agricultural University, College of Grassland Science and Technology, Beijing, China (and 1 more)
- Jie Wang 0018 — Nanjing University of Information Science and Technology, School of Electronic and Information Engineering, China (and 1 more)
- Jie Wang 0019 — Capital Normal University, School of Management, Beijing, China
- Jie Wang 0020 — Hebei University, College of Electronic and Information Engineering, Baoding, China (and 1 more)
- Jie Wang 0021 — Ping An Technology, Shenzhen, China
- Jie Wang 0022 — University of California, Computer Science Department, Los Angeles, CA, USA (and 1 more)
- Jie Wang 0023 — China Railway First Survey and Design Institute Group Co. Ltd, Xi'an, China (and 1 more)
- Jie Wang 0024 — Nanjing University of Posts and Telecommunications, College of Telecommunications and Information Engineering, Nanjing, China
- Jie Wang 0025 — Nanjing Medical University, Department of Radiology, Nanjing, China
- Jie Wang 0026 — Zhengzhou University, School of Electrical Engineering, Zhengzhou, China
- Jie Wang 0027 — Xinjiang University, Engineering Research Center for Renewable Energy Power Generation and Grid-connected Control, MOE, Urumqi, China
- Jie Wang 0028 — Ningbo University, College of Information Science and Engineering, Zhejiang, China
- Jie Wang 0029 — Nanjing University, School of Geography and Ocean Science, Nanjing, China
- Jie Wang 0030 — University of Massachusetts Amherst, Department of Mathematics and Statistics, Amherst, MA, USA
- Jie Wang 0031 — Sun Yat-sen University, School of Data and Computer Science, Guangdong Key Laboratory of Information Security, Guangzhou, China
- Jie Wang 0032 — Huaqiao University, School of Information Science and Engineering, Xiamen, China
- Jie Wang 0033 — University of Calgary, Department of Geomatics Engineering, Calgary, Canada
- Jie Wang 0034 — Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, Shanghai, China (and 1 more)
- Jie Wang 0035 — Chinese Academy of Sciences, Institute of Software, State Key Lab of Computer Sciences, Beijing, China
- Jie Wang 0036 — Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, State Key Laboratory of Remote Sensing Science, Beijing, China
- Jie Wang 0037 — LAAS-CNRS, Toulouse, France (and 2 more)
- Jie Wang 0038 — Peking University, LMAM & School of Mathematical Sciences, Beijing, China (and 1 more)
- Jie Wang 0039 — Zhejiang Institute of Economics and Trade College, School of Shangmao, Hangzhou City, China
- Jie Wang 0040 — Pusan National University, School of Mechanical Engineering, Busan, South Korea
- Jie Wang 0041 — National University of Defense Technology, College of Aerospace Science and Engineering, Changsha, China
- Jie Wang 0042 — Agency for Science, Technology and Research, Institute for Infocomm Research, Singapore (and 1 more)
- Jie Wang 0043 — Dalian University of Technology, School of Software, Dalian, China
- Jie Wang 0044 — Nanjing University, School of Information Management, Nanjing, China
- Jie Wang 0045 — Shanxi Normal University, College of Mathematics and Computer Science, Linfen, China
- Jie Wang 0046 — Shanxi University, School of Computer and Information Technology, Key Laboratory of Computational Intelligence and Chinese Information Processing, Shanxi, China
- Jie Wang 0047 — University of Science and Technology of China, Department of Automation, Hefei, China
- Jie Wang 0048 — Chinese University of Hong Kong, Department of Electronic Engineering, Robotics, Perception and Artificial Intelligence Lab, Hong Kong (and 1 more)
- Jie Wang 0049 — Chinese University of Hong Kong, School of Science and Engineering, Shenzhen, China (and 1 more)
- Jie Wang 0050 — Anhui University, School of Computer Science and Technology, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Hefei, China
- Jie Wang 0051 — Xi'an Jiao Tong University, School of Energy and Power Engineering, Xi'an, China (and 1 more)
- Jie Wang 0052 — Tongji University, School of Ocean and Earth Science, State Key Laboratory of Marine Geology, Shanghai, China
- Jie Wang 0053 — China Railway First Survey and Design Institute Group Co. Ltd., Xi'an, China
- Jie Wang 0054 — North China University of Science and Technology, School of Public Health, Tangshan, China
- Jie Wang 0055 — University of New South Wales, School of Biological, Earth and Environmental Science, Sydney, Australia
- Jie Wang 0056 — North China University of Technology, College of Science, Department of Statistics, Beijing, China (and 1 more)
- Jie Wang 0057 — Chinese Academy of Sciences, Chengdu Institute of Biology, Chengdu, China
- Jie Wang 0058 — Shenzhen Kaiyuan Internet Security Company Ltd., Shenzhen, China
- Jie Wang 0059 — University of Queensland, Business School, Brisbane, Australia
- Jie Wang 0060 — Anhui University, College of Resources and Environmental Engineering, Anhui Province Key Laboratory of Wetland Ecosystem Protection and Restoration, Hefei, China
- Jie Wang 0061 — University of Virginia, Department of Electrical and Computer Engineering, Charlottesville, VA, USA
- Jie Wang 0062 — Wuhan University of Science and Technology, School of Resource and Environmental Engineering, Wuhan, China
- Jie Wang 0063 — Zhejiang University, College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Hangzhou, China
- Jie Wang 0064 — Shanghai Aerospace Equipments Manufacturer Co., Ltd, Shanghai, China
- Jie Wang 0065 — Shanghai Jiaotong University, Koguan Law School, Shanghai, China
- Jie Wang 0066 — Chinese Academy of Sciences, Guangzhou Institutes of Biomedicine and Health, Guangzhou, China (and 1 more)
- Jie Wang 0067 — Central South University, School of Information Science and Engineering, Changsha, China
- Jie Wang 0068 — Wuhan University of Science and Technology, School of Computer Science and Technology, Wuhan, China
- Jie Wang 0069 — Nanjing University of Aeronautics and Astronautics, China
- Jie Wang 0070 — China Telecom Research Institute, Mobile Communication Research Department, Beijing, China
- Jie Wang 0071 — High-Tech Institute of Xi'an, College of Automation, China (and 1 more)
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2020 – today
- 2023
[j14]Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu:
Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1652-1667 (2023)- [c42]Qiyuan Liu, Qi Zhou, Rui Yang, Jie Wang:
Robust Representation Learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions. AAAI 2023: 8843-8851 - [c41]Zhihai Wang, Taoxing Pan, Qi Zhou, Jie Wang:
Efficient Exploration in Resource-Restricted Reinforcement Learning. AAAI 2023: 10279-10287 - [c40]Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu:
De Novo Molecular Generation via Connection-aware Motif Mining. ICLR 2023 - [c39]Zhihao Shi, Xize Liang, Jie Wang:
LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. ICLR 2023 - [c38]Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu:
Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. ICLR 2023 - [c37]Qi Zhou, Jie Wang, Qiyuan Liu, Yufei Kuang, Wengang Zhou, Houqiang Li:
Learning robust representation for reinforcement learning with distractions by reward sequence prediction. UAI 2023: 2551-2562 - [i46]Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu:
Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. CoRR abs/2302.00244 (2023) - [i45]Zhihao Shi, Xize Liang, Jie Wang:
LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. CoRR abs/2302.00924 (2023) - [i44]Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu:
De Novo Molecular Generation via Connection-aware Motif Mining. CoRR abs/2302.01129 (2023) - [i43]Jie Wang, Rui Yang, Zijie Geng, Zhihao Shi, Mingxuan Ye, Qi Zhou, Shuiwang Ji, Bin Li, Yongdong Zhang, Feng Wu:
Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution. CoRR abs/2302.09601 (2023) - [i42]Qiyuan Liu, Qi Zhou, Rui Yang, Jie Wang:
Robust Representation Learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions. CoRR abs/2302.12003 (2023) - [i41]Jie Wang, Zhihao Shi, Xize Liang, Shuiwang Ji, Bin Li, Feng Wu:
Provably Convergent Subgraph-wise Sampling for Fast GNN Training. CoRR abs/2303.11081 (2023) - [i40]Zhihai Wang, Lei Chen, Jie Wang, Xing Li, Yinqi Bai, Xijun Li, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu:
A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design. CoRR abs/2309.03208 (2023) - [i39]Jie Wang, Hanzhu Chen, Qitan Lv, Zhihao Shi, Jiajun Chen, Huarui He, Hongtao Xie, Yongdong Zhang, Feng Wu:
Learning Complete Topology-Aware Correlations Between Relations for Inductive Link Prediction. CoRR abs/2309.11528 (2023) - [i38]Zhihao Shi, Jie Wang, Fanghua Lu, Hanzhu Chen, Defu Lian, Zheng Wang, Jieping Ye, Feng Wu:
Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias. CoRR abs/2309.14907 (2023) - [i37]Zijie Geng, Xijun Li, Jie Wang, Xiao Li, Yongdong Zhang, Feng Wu:
A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability. CoRR abs/2310.02807 (2023) - [i36]Yufei Kuang, Xijun Li, Jie Wang, Fangzhou Zhu, Meng Lu, Zhihai Wang, Jia Zeng, Houqiang Li, Yongdong Zhang, Feng Wu:
Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning. CoRR abs/2310.11845 (2023) - [i35]Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, Feng Wu:
Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation. CoRR abs/2310.14161 (2023) - [i34]Mingxuan Ye, Yufei Kuang, Jie Wang, Rui Yang, Wengang Zhou, Houqiang Li, Feng Wu:
State Sequences Prediction via Fourier Transform for Representation Learning. CoRR abs/2310.15888 (2023) - 2022
- [j13]Hao Yuan, Lei Cai, Xia Hu, Jie Wang, Shuiwang Ji:
Interpreting Image Classifiers by Generating Discrete Masks. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 2019-2030 (2022) - [j12]Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji:
Line Graph Neural Networks for Link Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5103-5113 (2022) - [c36]Yufei Kuang, Miao Lu, Jie Wang, Qi Zhou, Bin Li, Houqiang Li:
Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization. AAAI 2022: 7247-7254 - [c35]Zhihai Wang, Jie Wang, Qi Zhou, Bin Li, Houqiang Li:
Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic. AAAI 2022: 8612-8620 - [c34]Huarui He, Jie Wang, Yunfei Liu, Feng Wu:
Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables. CIKM 2022: 717-726 - [c33]Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu:
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. KDD 2022: 534-544 - [c32]Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu:
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions. KDD 2022: 2242-2252 - [c31]Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu:
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. WWW 2022: 798-807 - [i33]Qingyu Qu, Xijun Li, Yunfan Zhou, Jia Zeng, Mingxuan Yuan, Jie Wang, Jinhu Lv, Kexin Liu, Kun Mao:
An Improved Reinforcement Learning Algorithm for Learning to Branch. CoRR abs/2201.06213 (2022) - [i32]Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu:
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. CoRR abs/2202.05679 (2022) - [i31]Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu:
Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings. CoRR abs/2203.12949 (2022) - [i30]Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu:
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions. CoRR abs/2205.10218 (2022) - [i29]Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu:
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. CoRR abs/2205.11678 (2022) - [i28]Xueliang Wang, Jiajun Chen, Feng Wu, Jie Wang:
Exploiting Global Semantic Similarities in Knowledge Graphs by Relational Prototype Entities. CoRR abs/2206.08021 (2022) - [i27]Xueliang Wang, Jianyu Cai, Shuiwang Ji, Houqiang Li, Feng Wu, Jie Wang:
Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification. CoRR abs/2206.08150 (2022) - [i26]Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji:
FlowX: Towards Explainable Graph Neural Networks via Message Flows. CoRR abs/2206.12987 (2022) - [i25]Huarui He, Jie Wang, Yunfei Liu, Feng Wu:
Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables. CoRR abs/2208.05482 (2022) - [i24]Zhihai Wang, Taoxing Pan, Qi Zhou, Jie Wang:
Efficient Exploration in Resource-Restricted Reinforcement Learning. CoRR abs/2212.06988 (2022) - 2021
- [j11]Shenghai Rong, Zilei Wang, Jie Wang:
Separated smooth sampling for fine-grained image classification. Neurocomputing 461: 350-359 (2021) - [j10]Ziqiang Li, Rentuo Tao, Jie Wang, Fu Li, Hongjing Niu, Mingdao Yue, Bin Li:
Interpreting the Latent Space of GANs via Measuring Decoupling. IEEE Trans. Artif. Intell. 2(1): 58-70 (2021) - [c30]Jiajun Chen, Huarui He, Feng Wu, Jie Wang:
Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. AAAI 2021: 6271-6278 - [c29]Jianyu Cai, Zhanqiu Zhang, Feng Wu, Jie Wang:
Deep Cognitive Reasoning Network for Multi-hop Question Answering over Knowledge Graphs. ACL/IJCNLP (Findings) 2021: 219-229 - [c28]Ning Wang, Wengang Zhou, Jie Wang, Houqiang Li:
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking. CVPR 2021: 1571-1580 - [c27]Xijun Li, Weilin Luo, Mingxuan Yuan, Jun Wang, Jiawen Lu, Jie Wang, Jinhu Lü, Jia Zeng:
Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems. ICDE 2021: 2511-2522 - [c26]Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji:
On Explainability of Graph Neural Networks via Subgraph Explorations. ICML 2021: 12241-12252 - [c25]Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu:
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. NeurIPS 2021: 19172-19183 - [i23]Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji:
On Explainability of Graph Neural Networks via Subgraph Explorations. CoRR abs/2102.05152 (2021) - [i22]Jiajun Chen, Huarui He, Feng Wu, Jie Wang:
Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. CoRR abs/2103.03642 (2021) - [i21]Ning Wang, Wengang Zhou, Jie Wang, Houqiang Li:
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking. CoRR abs/2103.11681 (2021) - [i20]Xijun Li, Weilin Luo, Mingxuan Yuan, Jun Wang, Jiawen Lu, Jie Wang, Jinhu Lu, Jia Zeng:
Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems. CoRR abs/2105.12899 (2021) - [i19]Jianyu Cai, Jiajun Chen, Taoxing Pan, Zhanqiu Zhang, Jie Wang:
Technical Report of Team GraphMIRAcles in the WikiKG90M-LSC Track of OGB-LSC @ KDD Cup 2021. CoRR abs/2107.05476 (2021) - [i18]Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu:
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. CoRR abs/2110.13715 (2021) - [i17]Zhihai Wang, Jie Wang, Qi Zhou, Bin Li, Houqiang Li:
Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic. CoRR abs/2112.10504 (2021) - [i16]Yufei Kuang, Miao Lu, Jie Wang, Qi Zhou, Bin Li, Houqiang Li:
Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization. CoRR abs/2112.10513 (2021) - 2020
- [c24]Taoxing Pan, Jun Liu, Jie Wang:
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. AAAI 2020: 1619-1626 - [c23]Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang:
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. AAAI 2020: 3065-3072 - [c22]Qi Zhou, Houqiang Li, Jie Wang:
Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization. AAAI 2020: 6941-6948 - [c21]Xueliang Wang, Feng Wu, Jie Wang:
Self-Adaptive Embedding For Few-Shot Classification By Hierarchical Attention. ICME 2020: 1-6 - [c20]Zhanqiu Zhang, Jianyu Cai, Jie Wang:
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. NeurIPS 2020 - [c19]Qi Zhou, Yufei Kuang, Zherui Qiu, Houqiang Li, Jie Wang:
Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method. NeurIPS 2020 - [i15]Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji:
Line Graph Neural Networks for Link Prediction. CoRR abs/2010.10046 (2020) - [i14]Zhanqiu Zhang, Jianyu Cai, Jie Wang:
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. CoRR abs/2011.05816 (2020)
2010 – 2019
- 2019
- [j9]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) - [j8]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) - [i13]Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang:
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. CoRR abs/1911.09419 (2019) - [i12]Qi Zhou, Houqiang Li, Jie Wang:
Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization. CoRR abs/1911.12574 (2019) - [i11]Taoxing Pan, Jun Liu, Jie Wang:
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. CoRR abs/1911.12665 (2019) - 2018
- [j7]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) - 2017
- [c18]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 - [c17]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 - [c16]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 - [i10]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) - 2016
- [j6]Yashu Liu, Jie Wang, Jieping Ye:
An Efficient Algorithm For Weak Hierarchical Lasso. ACM Trans. Knowl. Discov. Data 10(3): 32:1-32:24 (2016) - [c15]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 - [c14]Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang:
Parallel Lasso Screening for Big Data Optimization. KDD 2016: 1705-1714 - [c13]Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy:
A Multi-Task Learning Formulation for Survival Analysis. KDD 2016: 1715-1724 - [c12]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 - [i9]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) - [i8]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
- [j5]Jie Wang, Peter Wonka, Jieping Ye:
Lasso screening rules via dual polytope projection. J. Mach. Learn. Res. 16: 1063-1101 (2015) - [j4]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) - [c11]Jie Wang, Jieping Ye:
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices. ICML 2015: 1747-1756 - [c10]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 - [c9]Jie Wang, Jieping Ye:
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection. NIPS 2015: 1279-1287 - [i7]Jie Wang, Jieping Ye:
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices. CoRR abs/1505.04073 (2015) - 2014
- [c8]Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka, Jieping Ye:
A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models. ICML 2014: 235-243 - [c7]Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye:
Safe Screening with Variational Inequalities and Its Application to Lasso. ICML 2014: 289-297 - [c6]Jie Wang, Peter Wonka, Jieping Ye:
Scaling SVM and Least Absolute Deviations via Exact Data Reduction. ICML 2014: 523-531 - [c5]Yashu Liu, Jie Wang, Jieping Ye:
An efficient algorithm for weak hierarchical lasso. KDD 2014: 283-292 - [c4]Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye:
A Safe Screening Rule for Sparse Logistic Regression. NIPS 2014: 1053-1061 - [c3]Jie Wang, Jieping Ye:
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. NIPS 2014: 2132-2140 - [i6]Jie Wang, Jieping Ye:
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. CoRR abs/1410.4210 (2014) - 2013
- [c2]Sen Yang, Jie Wang, Wei Fan, Xiatian Zhang, Peter Wonka, Jieping Ye:
An efficient ADMM algorithm for multidimensional anisotropic total variation regularization problems. KDD 2013: 641-649 - [c1]Jie Wang, Jiayu Zhou, Peter Wonka, Jieping Ye:
Lasso Screening Rules via Dual Polytope Projection. NIPS 2013: 1070-1078 - [i5]Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye:
A Safe Screening Rule for Sparse Logistic Regression. CoRR abs/1307.4145 (2013) - [i4]Jie Wang, Jun Liu, Jieping Ye:
Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods. CoRR abs/1307.4156 (2013) - [i3]Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye:
Safe Screening With Variational Inequalities and Its Applicaiton to LASSO. CoRR abs/1307.7577 (2013) - [i2]Jie Wang, Peter Wonka, Jieping Ye:
Scaling SVM and Least Absolute Deviations via Exact Data Reduction. CoRR abs/1310.7048 (2013) - 2012
- [j3]Jie Wang, Xiaoqiang Wang:
VCells: Simple and Efficient Superpixels Using Edge-Weighted Centroidal Voronoi Tessellations. IEEE Trans. Pattern Anal. Mach. Intell. 34(6): 1241-1247 (2012) - [i1]Jie Wang, Peter Wonka, Jieping Ye:
Lasso Screening Rules via Dual Polytope Projection. CoRR abs/1211.3966 (2012) - 2011
- [j2]Jie Wang, Lili Ju, Xiaoqiang Wang:
Image Segmentation Using Local Variation and Edge-Weighted Centroidal Voronoi Tessellations. IEEE Trans. Image Process. 20(11): 3242-3256 (2011)
2000 – 2009
- 2009
- [j1]Jie Wang, Lili Ju, Xiaoqiang Wang:
An Edge-Weighted Centroidal Voronoi Tessellation Model for Image Segmentation. IEEE Trans. Image Process. 18(8): 1844-1858 (2009)
Coauthor Index
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