Jie Wang

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 78

Top Venues

Publications

Hanzhu Chen, Xu Shen, Qitan Lv, Jie Wang, Xiaoqi Ni, Jieping Ye
SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graph. ACL (1) (2024)
Hongyu Liu, Haoyang Liu, Yufei Kuang, Jie Wang, Bin Li
Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics. CoRR (2024)
Xize Liang, Chao Chen, Jie Wang, Yue Wu, Zhihang Fu, Zhihao Shi, Feng Wu, Jieping Ye
Robust Preference Optimization with Provable Noise Tolerance for LLMs. CoRR (2024)
Qianmei Liu, Yufei Kuang, Jie Wang
Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space. CoRR (2024)
Zhihai Wang, Zijie Geng, Zhaojie Tu, Jie Wang, Yuxi Qian, Zhexuan Xu, Ziyan Liu, Siyuan Xu, Zhentao Tang, Shixiong Kai, Mingxuan Yuan, Jianye Hao, Bin Li, Yongdong Zhang, Feng Wu
Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms. CoRR (2024)
Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye Hao, Bin Li, Feng Wu
Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework. ICLR (2024)
Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji
FlowX: Towards Explainable Graph Neural Networks via Message Flows. IEEE Trans. Pattern Anal. Mach. Intell. 46 (7) (2024)
Yu Huang, Min Zhou, Menglin Yang, Zhen Wang, Muhan Zhang, Jie Wang, Hong Xie, Hao Wang, Defu Lian, Enhong Chen
Foundations and Frontiers of Graph Learning Theory. CoRR (2024)
Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. ICLR (2024)
Jie Wang, Zhihai Wang, Xijun Li, Yufei Kuang, Zhihao Shi, Fangzhou Zhu, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu
Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. CoRR (2024)
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) (2023)
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 (2023)
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 (2023)
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)
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 (2023)
Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, Feng Wu
Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation. CoRR (2023)
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)
Mingxuan Ye, Yufei Kuang, Jie Wang, Rui Yang, Wengang Zhou, Houqiang Li, Feng Wu
State Sequences Prediction via Fourier Transform for Representation Learning. CoRR (2023)
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 (2023)
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 (2023)
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 (2023)
Qiyuan Liu, Qi Zhou, Rui Yang, Jie Wang
Robust Representation Learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions. AAAI (2023)
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)
Zhihao Shi, Xize Liang, Jie Wang
LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. ICLR (2023)
Zhihai Wang, Jie Wang, Qi Zhou, Bin Li, Houqiang Li
Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic. AAAI (2022)
Huarui He, Jie Wang, Yunfei Liu, Feng Wu
Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables. CIKM (2022)
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 (2022)
Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. WWW (2022)
Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. CoRR (2022)
Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. KDD (2022)
Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji
Line Graph Neural Networks for Link Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2022)
Xueliang Wang, Jianyu Cai, Shuiwang Ji, Houqiang Li, Feng Wu, Jie Wang
Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification. CoRR (2022)
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 (2022)
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) (2022)
Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu
Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings. CoRR (2022)
Zhihai Wang, Taoxing Pan, Qi Zhou, Jie Wang
Efficient Exploration in Resource-Restricted Reinforcement Learning. CoRR (2022)
Huarui He, Jie Wang, Yunfei Liu, Feng Wu
Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables. CoRR (2022)
Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji
On Explainability of Graph Neural Networks via Subgraph Explorations. CoRR (2021)
Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. CoRR (2021)
Jiajun Chen, Huarui He, Feng Wu, Jie Wang
Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. CoRR (2021)
Jiajun Chen, Huarui He, Feng Wu, Jie Wang
Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. AAAI (2021)
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 (2021)
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 (2021)
Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji
On Explainability of Graph Neural Networks via Subgraph Explorations. ICML (2021)
Zhihai Wang, Jie Wang, Qi Zhou, Bin Li, Houqiang Li
Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic. CoRR (2021)
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) (2021)
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 (2021)
Ning Wang, Wengang Zhou, Jie Wang, Houqiang Li
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking. CVPR (2021)
Ning Wang, Wengang Zhou, Jie Wang, Houqiang Li
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking. CoRR (2021)
Shenghai Rong, Zilei Wang, Jie Wang
Separated smooth sampling for fine-grained image classification. Neurocomputing 461 (2021)
Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. NeurIPS (2021)
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)
Jianyu Cai, Zhanqiu Zhang, Feng Wu, Jie Wang
Deep Cognitive Reasoning Network for Multi-hop Question Answering over Knowledge Graphs. ACL/IJCNLP (Findings) (2021)
Qi Zhou, Yufei Kuang, Zherui Qiu, Houqiang Li, Jie Wang
Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method. NeurIPS (2020)
Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. AAAI (2020)
Zhanqiu Zhang, Jianyu Cai, Jie Wang
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. NeurIPS (2020)
Zhanqiu Zhang, Jianyu Cai, Jie Wang
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. CoRR (2020)
Xueliang Wang, Feng Wu, Jie Wang
Self-Adaptive Embedding For Few-Shot Classification By Hierarchical Attention. ICME (2020)
Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji
Line Graph Neural Networks for Link Prediction. CoRR (2020)
Taoxing Pan, Jun Liu, Jie Wang
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. AAAI (2020)
Qi Zhou, Houqiang Li, Jie Wang
Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization. AAAI (2020)
Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. CoRR (2019)
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 (2019)
Taoxing Pan, Jun Liu, Jie Wang
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. CoRR (2019)
Jie Wang, Zhanqiu Zhang, Jieping Ye
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. J. Mach. Learn. Res. 20 (2019)
Qi Zhou, Houqiang Li, Jie Wang
Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization. CoRR (2019)
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) (2018)
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 (2017)
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)
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)
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)
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)
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 (2016)
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)
Yashu Liu, Jie Wang, Jieping Ye
An Efficient Algorithm For Weak Hierarchical Lasso. ACM Trans. Knowl. Discov. Data 10 (3) (2016)
Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang
Parallel Lasso Screening for Big Data Optimization. KDD (2016)
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 (2016)
Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy
A Multi-Task Learning Formulation for Survival Analysis. KDD (2016)
Jie Wang, Jieping Ye
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices. ICML (2015)
Jie Wang, Peter Wonka, Jieping Ye
Lasso screening rules via dual polytope projection. J. Mach. Learn. Res. 16 (2015)
Jie Wang, Wei Fan, Jieping Ye
Fused Lasso Screening Rules via the Monotonicity of Subdifferentials. IEEE Trans. Pattern Anal. Mach. Intell. 37 (9) (2015)
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)
Jie Wang, Jieping Ye
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices. CoRR (2015)
Jie Wang, Jieping Ye
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection. NIPS (2015)
Yashu Liu, Jie Wang, Jieping Ye
An efficient algorithm for weak hierarchical lasso. KDD (2014)
Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye
Safe Screening with Variational Inequalities and Its Application to Lasso. ICML (2014)
Jie Wang, Peter Wonka, Jieping Ye
Scaling SVM and Least Absolute Deviations via Exact Data Reduction. ICML (2014)
Jie Wang, Jieping Ye
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. NIPS (2014)
Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye
A Safe Screening Rule for Sparse Logistic Regression. NIPS (2014)
Jie Wang, Jieping Ye
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. CoRR (2014)
Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka, Jieping Ye
A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models. ICML (2014)
Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye
A Safe Screening Rule for Sparse Logistic Regression. CoRR (2013)
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)
Jie Wang, Jiayu Zhou, Peter Wonka, Jieping Ye
Lasso Screening Rules via Dual Polytope Projection. NIPS (2013)
Jie Wang, Jun Liu, Jieping Ye
Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods. CoRR (2013)
Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye
Safe Screening With Variational Inequalities and Its Applicaiton to LASSO. CoRR (2013)
Jie Wang, Peter Wonka, Jieping Ye
Scaling SVM and Least Absolute Deviations via Exact Data Reduction. CoRR (2013)
Jie Wang, Xiaoqiang Wang
VCells: Simple and Efficient Superpixels Using Edge-Weighted Centroidal Voronoi Tessellations. IEEE Trans. Pattern Anal. Mach. Intell. 34 (6) (2012)
Jie Wang, Peter Wonka, Jieping Ye
Lasso Screening Rules via Dual Polytope Projection CoRR (2012)
Jie Wang, Lili Ju, Xiaoqiang Wang
Image Segmentation Using Local Variation and Edge-Weighted Centroidal Voronoi Tessellations. IEEE Trans. Image Process. 20 (11) (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jie Wang