Jie Wang - RankMe

169 papers A* 59A 3B 1Journal 96Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning Deep Tree-Based Retriever for Efficient Recommendation: Theory and Method. IEEE Trans. Pattern Anal. Mach. Intell. Ze Liu, Jin Zhang, Defu Lian, Chao Feng, Jie Wang, Enhong Chen
2026	J	`jnl`	Why Attention Patterns Exist: A Unifying Temporal Perspective Analysis. CoRR Qingyue Yang, Jie Wang, Xing Li, Yinqi Bai, Xialiang Tong, Huiling Zhen, Jianye Hao, Mingxuan Yuan, Bin Li
2025	A*	`conf`	A Graph Enhanced Symbolic Discovery Framework For Efficient Logic Optimization. ICLR Yinqi Bai, Jie Wang, Lei Chen, Zhihai Wang, Yufei Kuang, Mingxuan Yuan, Jianye Hao, Feng Wu
2025	J	`jnl`	Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. Yufei Kuang, Xijun Li, Jie Wang, Fangzhou Zhu, Meng Lu, Zhihai Wang, Jia Zeng, Houqiang Li, Yongdong Zhang, Feng Wu
2025	A*	`conf`	Accelerating Large Language Model Reasoning via Speculative Search. ICML Zhihai Wang, Jie Wang, Jilai Pan, Xilin Xia, Huiling Zhen, Mingxuan Yuan, Jianye Hao, Feng Wu
2025	J	`jnl`	Accelerating Large Language Model Reasoning via Speculative Search. CoRR Zhihai Wang, Jie Wang, Jilai Pan, Xilin Xia, Huiling Zhen, Mingxuan Yuan, Jianye Hao, Feng Wu
2025	A*	`conf`	Accurate and Scalable Graph Neural Networks via Message Invariance. ICLR Zhihao Shi, Jie Wang, Zhiwei Zhuang, Xize Liang, Bin Li, Feng Wu
2025	J	`jnl`	Accurate and Scalable Graph Neural Networks via Message Invariance. CoRR Zhihao Shi, Jie Wang, Zhiwei Zhuang, Xize Liang, Bin Li, Feng Wu
2025	J	`jnl`	Advancing Symbolic Discovery on Unsupervised Data: A Pre-training Framework for Non-degenerate Implicit Equation Discovery. CoRR Yufei Kuang, Jie Wang, Huang Haotong, Mingxuan Ye, Fangzhou Zhu, Xijun Li, Jianye Hao, Wu Feng
2025	A*	`conf`	Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming. ICLR Haoyang Liu, Jie Wang, Zijie Geng, Xijun Li, Yuxuan Zong, Fangzhou Zhu, Jianye Hao, Feng Wu
2025	J	`jnl`	Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming. CoRR Haoyang Liu, Jie Wang, Zijie Geng, Xijun Li, Yuxuan Zong, Fangzhou Zhu, Jianye Hao, Feng Wu
2025	J	`jnl`	AttentionPredictor: Temporal Pattern Matters for Efficient LLM Inference. CoRR Qingyue Yang, Jie Wang, Xing Li, Zhihai Wang, Chen Chen, Lei Chen, Xianzhi Yu, Wulong Liu, Jianye Hao, Mingxuan Yuan, Bin Li
2025	A*	`conf`	Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples. ICML Xize Liang, Lin Yang, Jie Wang, Yiyang Lu, Runyu Wu, Hanzhu Chen, Jianye Hao
2025	J	`jnl`	CATI: A medical context-enhanced framework for diagnosis code assignment in the UK Biobank study. Artif. Intell. Medicine Yue Shen, Jie Wang, Zhe Wang, Zhihao Shi, Hanzhu Chen, Zheng Wang, Yukang Jiang, Xiaopu Wang, Chuandong Cheng, Xueqin Wang, Hongtu Zhu, Jieping Ye
2025	A*	`conf`	Computing Circuits Optimization via Model-Based Circuit Genetic Evolution. ICLR Zhihai Wang, Jie Wang, Xilin Xia, Dongsheng Zuo, Lei Chen, Yuzhe Ma, Jianye Hao, Mingxuan Yuan, Feng Wu
2025	A*	`conf`	Differentiable Integer Linear Programming. ICLR Zijie Geng, Jie Wang, Xijun Li, Fangzhou Zhu, Jianye Hao, Bin Li, Feng Wu
2025	A*	`conf`	HyperTree Planning: Enhancing LLM Reasoning via Hierarchical Thinking. ICML Runquan Gui, Zhihai Wang, Jie Wang, Chi Ma, Huiling Zhen, Mingxuan Yuan, Jianye Hao, Defu Lian, Enhong Chen, Feng Wu
2025	J	`jnl`	HyperTree Planning: Enhancing LLM Reasoning via Hierarchical Thinking. CoRR Runquan Gui, Zhihai Wang, Jie Wang, Chi Ma, Hui-Ling Zhen, Mingxuan Yuan, Jianye Hao, Defu Lian, Enhong Chen, Feng Wu
2025	A*	`conf`	Knowledge Graph Finetuning Enhances Knowledge Manipulation in Large Language Models. ICLR Hanzhu Chen, Xu Shen, Jie Wang, Zehao Wang, Qitan Lv, Junjie He, Rong Wu, Feng Wu, Jieping Ye
2025	A*	`conf`	LaMPlace: Learning to Optimize Cross-Stage Metrics in Macro Placement. ICLR Zijie Geng, Jie Wang, Ziyan Liu, Siyuan Xu, Zhentao Tang, Shixiong Kai, Mingxuan Yuan, Jianye Hao, Feng Wu
2025	A*	`conf`	Learning Robust Representations with Long-Term Information for Generalization in Visual Reinforcement Learning. ICLR Rui Yang, Jie Wang, Qijie Peng, Ruibo Guo, Guoping Wu, Bin Li
2025	J	`jnl`	Long-Term Feature Extraction via Frequency Prediction for Efficient Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. Jie Wang, Mingxuan Ye, Yufei Kuang, Rui Yang, Wengang Zhou, Houqiang Li, Feng Wu
2025	J	`jnl`	One Step Beyond: Feedthrough & Placement-Aware Rectilinear Floorplanner. CoRR Zhexuan Xu, Jie Wang, Siyuan Xu, Zijie Geng, Mingxuan Yuan, Feng Wu
2025	J	`jnl`	OptiTree: Hierarchical Thoughts Generation with Tree Search for LLM Optimization Modeling. CoRR Haoyang Liu, Jie Wang, Yuyang Cai, Xiongwei Han, Yufei Kuang, Jianye Hao
2025	J	`jnl`	Piano: A Multi-Constraint Pin Assignment-Aware Floorplanner. CoRR Zhexuan Xu, Kexin Zhou, Jie Wang, Zijie Geng, Siyuan Xu, Shixiong Kai, Mingxuan Yuan, Feng Wu
2025	A*	`conf`	ROPO: Robust Preference Optimization for Large Language Models. ICML Xize Liang, Chao Chen, Shuang Qiu, Jie Wang, Yue Wu, Zhihang Fu, Hanzhu Chen, Feng Wu, Jieping Ye
2025	J	`jnl`	RoME: Domain-Robust Mixture-of-Experts for MILP Solution Prediction across Domains. CoRR Tianle Pu, Zijie Geng, Haoyang Liu, Shixuan Liu, Jie Wang, Li Zeng, Chao Chen, Changjun Fan
2024	A*	`conf`	A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design. ICML Zhihai Wang, Lei Chen, Jie Wang, Yinqi Bai, Xing Li, Xijun Li, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu
2024	A*	`conf`	A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design. ICML Zhihai Wang, Jie Wang, Dongsheng Zuo, Yunjie Ji, Xilin Xia, Yuzhe Ma, Jianye Hao, Mingxuan Yuan, Yongdong Zhang, Feng Wu
2024	A*	`conf`	Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. ICLR Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
2024	J	`jnl`	Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling. CoRR Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
2024	A*	`conf`	Accelerating PDE Data Generation via Differential Operator Action in Solution Space. ICML Huanshuo Dong, Hong Wang, Haoyang Liu, Jian Luo, Jie Wang
2024	J	`jnl`	Accelerating PDE Data Generation via Differential Operator Action in Solution Space. CoRR Huanshuo Dong, Hong Wang, Haoyang Liu, Jian Luo, Jie Wang
2024	J	`jnl`	Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms. CoRR 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
2024	A*	`conf`	Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models. ICML Qitan Lv, Jie Wang, Hanzhu Chen, Bin Li, Yongdong Zhang, Feng Wu
2024	J	`jnl`	Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models. CoRR Qitan Lv, Jie Wang, Hanzhu Chen, Bin Li, Yongdong Zhang, Feng Wu
2024	—	`conf`	Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics. GECCO Companion Hongyu Liu, Haoyang Liu, Yufei Kuang, Jie Wang, Bin Li
2024	J	`jnl`	Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics. CoRR Hongyu Liu, Haoyang Liu, Yufei Kuang, Jie Wang, Bin Li
2024	J	`jnl`	Deep Tree-based Retrieval for Efficient Recommendation: Theory and Method. CoRR Ze Liu, Jin Zhang, Chao Feng, Defu Lian, Jie Wang, Enhong Chen
2024	J	`jnl`	FlowX: Towards Explainable Graph Neural Networks via Message Flows. IEEE Trans. Pattern Anal. Mach. Intell. Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji
2024	J	`jnl`	Foundations and Frontiers of Graph Learning Theory. CoRR Yu Huang, Min Zhou, Menglin Yang, Zhen Wang, Muhan Zhang, Jie Wang, Hong Xie, Hao Wang, Defu Lian, Enhong Chen
2024	J	`jnl`	Label Deconvolution for Node Representation Learning on Large-Scale Attributed Graphs Against Learning Bias. IEEE Trans. Pattern Anal. Mach. Intell. Zhihao Shi, Jie Wang, Fanghua Lu, Hanzhu Chen, Defu Lian, Zheng Wang, Jieping Ye, Feng Wu
2024	J	`jnl`	Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction. CoRR Tianyu Liu, Qitan Lv, Jie Wang, Shuling Yang, Hanzhu Chen
2024	J	`jnl`	Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. CoRR Jie Wang, Zhihai Wang, Xijun Li, Yufei Kuang, Zhihao Shi, Fangzhou Zhu, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu
2024	J	`jnl`	Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. IEEE Trans. Pattern Anal. Mach. Intell. Jie Wang, Zhihai Wang, Xijun Li, Yufei Kuang, Zhihao Shi, Fangzhou Zhu, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu
2024	A*	`conf`	Learning to Stop Cut Generation for Efficient Mixed-Integer Linear Programming. AAAI Haotian Ling, Zhihai Wang, Jie Wang
2024	J	`jnl`	Learning to Stop Cut Generation for Efficient Mixed-Integer Linear Programming. CoRR Haotian Ling, Zhihai Wang, Jie Wang
2024	A*	`conf`	MILP-StuDio: MILP Instance Generation via Block Structure Decomposition. NeurIPS Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu
2024	J	`jnl`	MILP-StuDio: MILP Instance Generation via Block Structure Decomposition. CoRR Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu
2024	J	`jnl`	Machine Learning Insides OptVerse AI Solver: Design Principles and Applications. CoRR Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, Weilin Luo, Meng Lu, Yimin Huang, Zhenan Fan, Zirui Zhou, Yufei Kuang, Zhihai Wang, Zijie Geng, Yang Li, Haoyang Liu, Zhiwu An, Muming Yang, Jianshu Li, Jie Wang, Junchi Yan, Defeng Sun, Tao Zhong, Yong Zhang, Jia Zeng, Mingxuan Yuan, Jianye Hao, Jun Yao, Kun Mao
2024	J	`jnl`	Multi-agent Multi-armed Bandits with Stochastic Sharable Arm Capacities. CoRR Hong Xie, Jinyu Mo, Defu Lian, Jie Wang, Enhong Chen
2024	A*	`conf`	Neural Krylov Iteration for Accelerating Linear System Solving. NeurIPS Jian Luo, Jie Wang, Hong Wang, Huanshuo Dong, Zijie Geng, Hanzhu Chen, Yufei Kuang
2024	A*	`conf`	Reinforcement Learning within Tree Search for Fast Macro Placement. ICML Zijie Geng, Jie Wang, Ziyan Liu, Siyuan Xu, Zhentao Tang, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu
2024	A*	`conf`	Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework. ICLR Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye Hao, Bin Li, Feng Wu
2024	B	`conf`	Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space. IJCNN Qianmei Liu, Yufei Kuang, Jie Wang
2024	J	`jnl`	Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space. CoRR Qianmei Liu, Yufei Kuang, Jie Wang
2024	J	`jnl`	Robust Preference Optimization with Provable Noise Tolerance for LLMs. CoRR Xize Liang, Chao Chen, Jie Wang, Yue Wu, Zhihang Fu, Zhihao Shi, Feng Wu, Jieping Ye
2024	—	`conf`	SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graph. ACL (1) Hanzhu Chen, Xu Shen, Qitan Lv, Jie Wang, Xiaoqi Ni, Jieping Ye
2024	J	`jnl`	SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graphs. CoRR Hanzhu Chen, Xu Shen, Qitan Lv, Jie Wang, Xiaoqi Ni, Jieping Ye
2024	A*	`conf`	Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph. ICML Yufei Kuang, Jie Wang, Yuyan Zhou, Xijun Li, Fangzhou Zhu, Jianye Hao, Feng Wu
2024	A*	`conf`	Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework. NeurIPS Zhihai Wang, Jie Wang, Qingyue Yang, Yinqi Bai, Xing Li, Lei Chen, Jianye Hao, Mingxuan Yuan, Bin Li, Yongdong Zhang, Feng Wu
2024	J	`jnl`	Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions. CoRR Rui Yang, Jie Wang, Guoping Wu, Bin Li
2023	J	`jnl`	A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design. CoRR Zhihai Wang, Lei Chen, Jie Wang, Xing Li, Yinqi Bai, Xijun Li, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu
2023	A*	`conf`	A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability. NeurIPS Zijie Geng, Xijun Li, Jie Wang, Xiao Li, Yongdong Zhang, Feng Wu
2023	J	`jnl`	A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability. CoRR Zijie Geng, Xijun Li, Jie Wang, Xiao Li, Yongdong Zhang, Feng Wu
2023	J	`jnl`	Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning. CoRR Yufei Kuang, Xijun Li, Jie Wang, Fangzhou Zhu, Meng Lu, Zhihai Wang, Jia Zeng, Houqiang Li, Yongdong Zhang, Feng Wu
2023	A*	`conf`	De Novo Molecular Generation via Connection-aware Motif Mining. ICLR Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu
2023	J	`jnl`	De Novo Molecular Generation via Connection-aware Motif Mining. CoRR Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu
2023	J	`jnl`	Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings. IEEE Trans. Pattern Anal. Mach. Intell. Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu
2023	A*	`conf`	Efficient Exploration in Resource-Restricted Reinforcement Learning. AAAI Zhihai Wang, Taoxing Pan, Qi Zhou, Jie Wang
2023	J	`jnl`	Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution. CoRR Jie Wang, Rui Yang, Zijie Geng, Zhihao Shi, Mingxuan Ye, Qi Zhou, Shuiwang Ji, Bin Li, Yongdong Zhang, Feng Wu
2023	A*	`conf`	LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. ICLR Zhihao Shi, Xize Liang, Jie Wang
2023	J	`jnl`	LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. CoRR Zhihao Shi, Xize Liang, Jie Wang
2023	J	`jnl`	Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias. CoRR Zhihao Shi, Jie Wang, Fanghua Lu, Hanzhu Chen, Defu Lian, Zheng Wang, Jieping Ye, Feng Wu
2023	J	`jnl`	Learning Complete Topology-Aware Correlations Between Relations for Inductive Link Prediction. CoRR Jie Wang, Hanzhu Chen, Qitan Lv, Zhihao Shi, Jiajun Chen, Huarui He, Hongtao Xie, Yongdong Zhang, Feng Wu
2023	A*	`conf`	Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. ICLR Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu
2023	J	`jnl`	Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. CoRR Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu
2023	A*	`conf`	Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction. NeurIPS Tianyu Liu, Qitan Lv, Jie Wang, Shuling Yang, Hanzhu Chen
2023	A	`conf`	Learning robust representation for reinforcement learning with distractions by reward sequence prediction. UAI Qi Zhou, Jie Wang, Qiyuan Liu, Yufei Kuang, Wengang Zhou, Houqiang Li
2023	J	`jnl`	Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation. CoRR Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, Feng Wu
2023	J	`jnl`	Provably Convergent Subgraph-wise Sampling for Fast GNN Training. CoRR Jie Wang, Zhihao Shi, Xize Liang, Shuiwang Ji, Bin Li, Feng Wu
2023	—	`conf`	Real-Time Information Extraction for Phone Review in Car Loan Audit. DASFAA (4) Hongxuan Liu, Jie Wang, Yansong Wang, Shuling Yang, Hanzhu Chen, Binbin Fang
2023	A*	`conf`	Robust Representation Learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions. AAAI Qiyuan Liu, Qi Zhou, Rui Yang, Jie Wang
2023	J	`jnl`	Robust Representation Learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions. CoRR Qiyuan Liu, Qi Zhou, Rui Yang, Jie Wang
2023	A*	`conf`	State Sequences Prediction via Fourier Transform for Representation Learning. NeurIPS Mingxuan Ye, Yufei Kuang, Jie Wang, Yang rui, Wengang Zhou, Houqiang Li, Feng Wu
2023	J	`jnl`	State Sequences Prediction via Fourier Transform for Representation Learning. CoRR Mingxuan Ye, Yufei Kuang, Jie Wang, Rui Yang, Wengang Zhou, Houqiang Li, Feng Wu
2022	J	`jnl`	An Improved Reinforcement Learning Algorithm for Learning to Branch. CoRR Qingyu Qu, Xijun Li, Yunfan Zhou, Jia Zeng, Mingxuan Yuan, Jie Wang, Jinhu Lv, Kexin Liu, Kun Mao
2022	A*	`conf`	Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. KDD Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu
2022	J	`jnl`	Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation. CoRR Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu
2022	J	`jnl`	Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings. CoRR Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu
2022	J	`jnl`	Efficient Exploration in Resource-Restricted Reinforcement Learning. CoRR Zhihai Wang, Taoxing Pan, Qi Zhou, Jie Wang
2022	J	`jnl`	Exploiting Global Semantic Similarities in Knowledge Graphs by Relational Prototype Entities. CoRR Xueliang Wang, Jiajun Chen, Feng Wu, Jie Wang
2022	J	`jnl`	FlowX: Towards Explainable Graph Neural Networks via Message Flows. CoRR Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji
2022	J	`jnl`	Interpreting Image Classifiers by Generating Discrete Masks. IEEE Trans. Pattern Anal. Mach. Intell. Hao Yuan, Lei Cai, Xia Hu, Jie Wang, Shuiwang Ji
2022	A*	`conf`	Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization. AAAI Yufei Kuang, Miao Lu, Jie Wang, Qi Zhou, Bin Li, Houqiang Li
2022	A*	`conf`	Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions. KDD Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu
2022	J	`jnl`	Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions. CoRR Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu
2022	J	`jnl`	Learning to Reformulate for Linear Programming. CoRR Xijun Li, Qingyu Qu, Fangzhou Zhu, Jia Zeng, Mingxuan Yuan, Kun Mao, Jie Wang
2022	J	`jnl`	Line Graph Neural Networks for Link Prediction. IEEE Trans. Pattern Anal. Mach. Intell. Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji
2022	A	`conf`	Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables. CIKM Huarui He, Jie Wang, Yunfei Liu, Feng Wu
2022	J	`jnl`	Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables. CoRR Huarui He, Jie Wang, Yunfei Liu, Feng Wu
2022	A*	`conf`	Rethinking Graph Convolutional Networks in Knowledge Graph Completion. WWW Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu
2022	J	`jnl`	Rethinking Graph Convolutional Networks in Knowledge Graph Completion. CoRR Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu
2022	A*	`conf`	Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic. AAAI Zhihai Wang, Jie Wang, Qi Zhou, Bin Li, Houqiang Li
2022	J	`jnl`	Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification. CoRR Xueliang Wang, Jianyu Cai, Shuiwang Ji, Houqiang Li, Feng Wu, Jie Wang
2021	A*	`conf`	ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. NeurIPS Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu
2021	J	`jnl`	ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. CoRR Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu
2021	—	`conf`	Deep Cognitive Reasoning Network for Multi-hop Question Answering over Knowledge Graphs. ACL/IJCNLP (Findings) Jianyu Cai, Zhanqiu Zhang, Feng Wu, Jie Wang
2021	J	`jnl`	Interpreting the Latent Space of GANs via Measuring Decoupling. IEEE Trans. Artif. Intell. Ziqiang Li, Rentuo Tao, Jie Wang, Fu Li, Hongjing Niu, Mingdao Yue, Bin Li
2021	J	`jnl`	Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization. CoRR Yufei Kuang, Miao Lu, Jie Wang, Qi Zhou, Bin Li, Houqiang Li
2021	A*	`conf`	Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems. ICDE Xijun Li, Weilin Luo, Mingxuan Yuan, Jun Wang, Jiawen Lu, Jie Wang, Jinhu Lü, Jia Zeng
2021	J	`jnl`	Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems. CoRR Xijun Li, Weilin Luo, Mingxuan Yuan, Jun Wang, Jiawen Lu, Jie Wang, Jinhu Lu, Jia Zeng
2021	A*	`conf`	On Explainability of Graph Neural Networks via Subgraph Explorations. ICML Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji
2021	J	`jnl`	On Explainability of Graph Neural Networks via Subgraph Explorations. CoRR Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji
2021	J	`jnl`	Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic. CoRR Zhihai Wang, Jie Wang, Qi Zhou, Bin Li, Houqiang Li
2021	J	`jnl`	Separated smooth sampling for fine-grained image classification. Neurocomputing Shenghai Rong, Zilei Wang, Jie Wang
2021	J	`jnl`	Technical Report of Team GraphMIRAcles in the WikiKG90M-LSC Track of OGB-LSC @ KDD Cup 2021. CoRR Jianyu Cai, Jiajun Chen, Taoxing Pan, Zhanqiu Zhang, Jie Wang
2021	A*	`conf`	Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. AAAI Jiajun Chen, Huarui He, Feng Wu, Jie Wang
2021	J	`jnl`	Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. CoRR Jiajun Chen, Huarui He, Feng Wu, Jie Wang
2021	A*	`conf`	Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking. CVPR Ning Wang, Wengang Zhou, Jie Wang, Houqiang Li
2021	J	`jnl`	Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking. CoRR Ning Wang, Wengang Zhou, Jie Wang, Houqiang Li
2020	A*	`conf`	D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. AAAI Taoxing Pan, Jun Liu, Jie Wang
2020	A*	`conf`	Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization. AAAI Qi Zhou, Houqiang Li, Jie Wang
2020	A*	`conf`	Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. NeurIPS Zhanqiu Zhang, Jianyu Cai, Jie Wang
2020	J	`jnl`	Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. CoRR Zhanqiu Zhang, Jianyu Cai, Jie Wang
2020	A*	`conf`	Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. AAAI Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang
2020	J	`jnl`	Line Graph Neural Networks for Link Prediction. CoRR Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji
2020	A*	`conf`	Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method. NeurIPS Qi Zhou, Yufei Kuang, Zherui Qiu, Houqiang Li, Jie Wang
2020	A	`conf`	Self-Adaptive Embedding For Few-Shot Classification By Hierarchical Attention. ICME Xueliang Wang, Feng Wu, Jie Wang
2019	J	`jnl`	D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems. CoRR Taoxing Pan, Jun Liu, Jie Wang
2019	J	`jnl`	Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization. CoRR Qi Zhou, Houqiang Li, Jie Wang
2019	J	`jnl`	Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. CoRR Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang
2019	J	`jnl`	Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction. J. Mach. Learn. Res. Bin Hong, Weizhong Zhang, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang
2019	J	`jnl`	Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. J. Mach. Learn. Res. Jie Wang, Zhanqiu Zhang, Jieping Ye
2018	J	`jnl`	Identifying Genetic Risk Factors for Alzheimer's Disease via Shared Tree-Guided Feature Learning Across Multiple Tasks. IEEE Trans. Knowl. Data Eng. Weizhong Zhang, Tingjin Luo, Shuang Qiu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang
2017	A*	`conf`	Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning. KDD Tingjin Luo, Weizhong Zhang, Shang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye, Jie Wang
2017	J	`jnl`	Large-scale Feature Selection of Risk Genetic Factors for Alzheimer's Disease via Distributed Group Lasso Regression. CoRR Qingyang Li, Dajiang Zhu, Jie Zhang, Derrek Paul Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang
2017	A*	`conf`	Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction. ICML Weizhong Zhang, Bin Hong, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang
2017	A*	`conf`	The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms. KDD Yongxin Tong, Yuqiang Chen, Zimu Zhou, Lei Chen, Jie Wang, Qiang Yang, Jieping Ye, Weifeng Lv
2016	A*	`conf`	A Multi-Task Learning Formulation for Survival Analysis. KDD Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy
2016	J	`jnl`	An Efficient Algorithm For Weak Hierarchical Lasso. ACM Trans. Knowl. Discov. Data Yashu Liu, Jie Wang, Jieping Ye
2016	—	`conf`	Large-Scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions. MICCAI (1) Qingyang Li, Tao Yang, Liang Zhan, Derrek P. Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang
2016	J	`jnl`	Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions. CoRR Qingyang Li, Tao Yang, Liang Zhan, Derrek P. Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang
2016	A*	`conf`	Parallel Lasso Screening for Big Data Optimization. KDD Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang
2016	J	`jnl`	Scaling Up Sparse Support Vector Machine by Simultaneous Feature and Sample Reduction. CoRR Weizhong Zhang, Bin Hong, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang
2016	A*	`conf`	Transfer Learning for Survival Analysis via Efficient L2, 1-Norm Regularized Cox Regression. ICDM Yan Li, Lu Wang, Jie Wang, Jieping Ye, Chandan K. Reddy
2015	—	`conf`	Detecting genetic risk factors for Alzheimer's disease in whole genome sequence data via Lasso screening. ISBI Tao Yang, Jie Wang, Qian Sun, Derrek P. Hibar, Neda Jahanshad, Li Liu, Yalin Wang, Liang Zhan, Paul M. Thompson, Jieping Ye
2015	J	`jnl`	Fused Lasso Screening Rules via the Monotonicity of Subdifferentials. IEEE Trans. Pattern Anal. Mach. Intell. Jie Wang, Wei Fan, Jieping Ye
2015	J	`jnl`	Lasso screening rules via dual polytope projection. J. Mach. Learn. Res. Jie Wang, Peter Wonka, Jieping Ye
2015	—	`conf`	Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection. NIPS Jie Wang, Jieping Ye
2015	A*	`conf`	Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices. ICML Jie Wang, Jieping Ye
2015	J	`jnl`	Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices. CoRR Jie Wang, Jieping Ye
2014	A*	`conf`	A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models. ICML Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka, Jieping Ye
2014	—	`conf`	A Safe Screening Rule for Sparse Logistic Regression. NIPS Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye
2014	A*	`conf`	An efficient algorithm for weak hierarchical lasso. KDD Yashu Liu, Jie Wang, Jieping Ye
2014	A*	`conf`	Safe Screening with Variational Inequalities and Its Application to Lasso. ICML Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye
2014	A*	`conf`	Scaling SVM and Least Absolute Deviations via Exact Data Reduction. ICML Jie Wang, Peter Wonka, Jieping Ye
2014	—	`conf`	Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. NIPS Jie Wang, Jieping Ye
2014	J	`jnl`	Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. CoRR Jie Wang, Jieping Ye
2013	J	`jnl`	A Safe Screening Rule for Sparse Logistic Regression. CoRR Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye
2013	A*	`conf`	An efficient ADMM algorithm for multidimensional anisotropic total variation regularization problems. KDD Sen Yang, Jie Wang, Wei Fan, Xiatian Zhang, Peter Wonka, Jieping Ye
2013	J	`jnl`	Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods. CoRR Jie Wang, Jun Liu, Jieping Ye
2013	—	`conf`	Lasso Screening Rules via Dual Polytope Projection. NIPS Jie Wang, Jiayu Zhou, Peter Wonka, Jieping Ye
2013	J	`jnl`	Safe Screening With Variational Inequalities and Its Applicaiton to LASSO. CoRR Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye
2013	J	`jnl`	Scaling SVM and Least Absolute Deviations via Exact Data Reduction. CoRR Jie Wang, Peter Wonka, Jieping Ye
2012	J	`jnl`	Lasso Screening Rules via Dual Polytope Projection CoRR Jie Wang, Peter Wonka, Jieping Ye
2012	J	`jnl`	VCells: Simple and Efficient Superpixels Using Edge-Weighted Centroidal Voronoi Tessellations. IEEE Trans. Pattern Anal. Mach. Intell. Jie Wang, Xiaoqiang Wang
2011	J	`jnl`	Image Segmentation Using Local Variation and Edge-Weighted Centroidal Voronoi Tessellations. IEEE Trans. Image Process. Jie Wang, Lili Ju, Xiaoqiang Wang
2009	J	`jnl`	An Edge-Weighted Centroidal Voronoi Tessellation Model for Image Segmentation. IEEE Trans. Image Process. Jie Wang, Lili Ju, Xiaoqiang Wang