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ORCIDMing Zhang 0004
张铭
Person information
- unicode name: 张铭
- affiliation (PhD 2005): Peking University, School of Computer Science, Beijing, China
Other persons with the same name
- Ming Zhang — disambiguation page
- Ming Zhang 0001 — Zhejiang University, Institute of Information and Communication Engineering, Hangzhou, China (and 1 more)
- Ming Zhang 0002
![[0000-0002-6027-4594]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-6027-4594")
— Hong Kong Polytechnic University, Department of Health Technology & Information, Hong Kong - Ming Zhang 0003 — Harbin Engineering University, College of Information and Telecommunication, China
- Ming Zhang 0005 — Alibaba Group (and 1 more)
- Ming Zhang 0006 — University of Ottawa, PARADISE Research Laboratory, ON, Canada (and 1 more)
- Ming Zhang 0007 — University of Paris-Sud, Orsay, France
- Ming Zhang 0008 — Texas A&M University, Department of Computer Science, College Station, TX, USA
- Ming Zhang 0009 — Huazhong University of Science and Technology, School of Electrical and Electronic Engineering, Wuhan, China
- Ming Zhang 0010 — Xi'an Jiaotong University, School of Electronic and Information Engineering, China
- Ming Zhang 0011 — Harbin Institute of Technology, School of Electrical Engineering and Automation, China
- Ming Zhang 0012 — Xidian University, State Key Laboratory of Integrated Services Networks, Xi'an, China
- Ming Zhang 0013 — Anhui Polytechnic University, Wuhu, China
- Ming Zhang 0014 — Tsinghua University, Department of Precision Instruments and Mechanology, Beijing, China
- Ming Zhang 0015 — Aston University. Birmingham, UK (and 1 more)
- Ming Zhang 0016 — Mindray, Nanshan, China (and 1 more)
- Ming Zhang 0017 — Intel, CA, USA (and 1 more)
- Ming Zhang 0018 — Zhejiang University, Hangzhou, China
- Ming Zhang 0019 — China University of Geosciences, Wuhan, China
- Ming Zhang 0020 — Christopher Newport University, Department of Physics, Computer Science and Engineering, VA, 23606, USA
- Ming Zhang 0021 — National Key Laboratory of Science and Technology, Beijing Information System Security, China
- Ming Zhang 0022 — Nanjing University of Aeronautics and Astronautics, College of General Aviation and Flight, China
- Ming Zhang 0023 — City University of Hong Kong, Centre for Intelligent Multidimensional Data Analysis Limited, Department of Electrical Engineering, Hong Kong
- Ming Zhang 0024 — Southeast University, China
- Ming Zhang 0025 — Dalian Maritime University, Information Science and Technology College, China (and 1 more)
- Ming Zhang 0026 — Virtustream (and 1 more)
- Ming Zhang 0027 — National University of Defense Technology, College of Artificial Intelligence, College of Mechatronic Engineering and Automation, Changsha, China
- Ming Zhang 0028 — University of Florida, Department of Computer and Information Science and Engineering, Gainesville, FL, USA
- Ming Zhang 0029 — University of Science and Technology of China, CAS Key Laboratory of Wireless-Optical Communications, Hefei, China
- Ming Zhang 0030 — Fudan University, Shanghai, China
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2020 – today
- 2024
[j35]Wei Ju, Yusheng Zhao, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, Ming Zhang:
COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting. Inf. Fusion 107: 102341 (2024)- [j34]Yutong Liu, Qiao Xiang, Juan Chen, Ming Zhang, Jingdong Xu, Yuan Luo:
Undergraduate Computer Science Education in China. Inroads 15(1): 28-36 (2024) - [j33]Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, Ming Zhang:
A Comprehensive Survey on Deep Graph Representation Learning. Neural Networks 173: 106207 (2024) - [j32]Wei Ju, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Siyu Yi, Zhiping Xiao, Xiao Luo, Yanjie Fu, Ming Zhang:
Focus on informative graphs! Semi-supervised active learning for graph-level classification. Pattern Recognit. 153: 110567 (2024) - [j31]Xiao Luo, Daqing Wu, Yiyang Gu, Chong Chen, Luchen Liu, Jinwen Ma, Ming Zhang, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua:
Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation. ACM Trans. Knowl. Discov. Data 18(1): 14:1-14:26 (2024) - [j30]Xiao Luo, Wei Ju, Yiyang Gu, Zhengyang Mao, Luchen Liu, Yuhui Yuan, Ming Zhang:
Self-supervised Graph-level Representation Learning with Adversarial Contrastive Learning. ACM Trans. Knowl. Discov. Data 18(2): 34:1-34:23 (2024) - [j29]Xiao Luo, Yusheng Zhao, Yifang Qin, Wei Ju, Ming Zhang:
Towards Semi-Supervised Universal Graph Classification. IEEE Trans. Knowl. Data Eng. 36(1): 416-428 (2024) - [j28]Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo, Ming Zhang:
Learning Graph ODE for Continuous-Time Sequential Recommendation. IEEE Trans. Knowl. Data Eng. 36(7): 3224-3236 (2024) - [j27]Xiao Luo, Wei Ju, Meng Qu, Yiyang Gu, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
CLEAR: Cluster-Enhanced Contrast for Self-Supervised Graph Representation Learning. IEEE Trans. Neural Networks Learn. Syst. 35(1): 899-912 (2024) - [j26]Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang:
A Diffusion Model for POI Recommendation. ACM Trans. Inf. Syst. 42(2): 54:1-54:27 (2024) - [j25]Xiao Luo, Wei Ju, Yiyang Gu, Yifang Qin, Siyu Yi, Daqing Wu, Luchen Liu, Ming Zhang:
Toward Effective Semi-supervised Node Classification with Hybrid Curriculum Pseudo-labeling. ACM Trans. Multim. Comput. Commun. Appl. 20(3): 82:1-82:19 (2024) - [c167]Yu Pan, Ye Yuan, Yichun Yin, Jiaxin Shi, Zenglin Xu, Ming Zhang, Lifeng Shang, Xin Jiang, Qun Liu:
Preparing Lessons for Progressive Training on Language Models. AAAI 2024: 18860-18868 - [c166]Wei Ju, Siyu Yi, Ming Zhang:
Evidential Self-Supervised Graph Representation Learning via Prototype-based Consistency. ACM TUR-C 2024 - [c165]Jianhao Shen, Ye Yuan, Srbuhi Mirzoyan, Ming Zhang, Chenguang Wang:
Measuring Vision-Language STEM Skills of Neural Models. ICLR 2024 - [c164]Xiao Luo, Yiyang Gu, Huiyu Jiang, Hang Zhou, Jinsheng Huang, Wei Ju, Zhiping Xiao, Ming Zhang, Yizhou Sun:
PGODE: Towards High-quality System Dynamics Modeling. ICML 2024 - [c163]Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, Ming Zhang:
Hypergraph-enhanced Dual Semi-supervised Graph Classification. ICML 2024 - [c162]Junwei Yang, Kangjie Zheng, Siyu Long, Zaiqing Nie, Ming Zhang, Xinyu Dai, Wei-Ying Ma, Hao Zhou:
Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective. ICML 2024 - [c161]Kangjie Zheng, Siyu Long, Tianyu Lu, Junwei Yang, Xinyu Dai, Ming Zhang, Zaiqing Nie, Wei-Ying Ma, Hao Zhou:
ESM All-Atom: Multi-Scale Protein Language Model for Unified Molecular Modeling. ICML 2024 - [c160]Ye Yuan, Kexin Tang, Jianhao Shen, Ming Zhang, Chenguang Wang:
Measuring Social Norms of Large Language Models. NAACL-HLT (Findings) 2024: 650-699 - [i81]Hourun Li, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Zhiping Xiao, Jiaqi Feng, Yiyang Gu, Wei Ju, Xiao Luo, Ming Zhang:
A Survey on Graph Neural Networks in Intelligent Transportation Systems. CoRR abs/2401.00713 (2024) - [i80]Yu Pan, Ye Yuan, Yichun Yin, Jiaxin Shi, Zenglin Xu, Ming Zhang, Lifeng Shang, Xin Jiang, Qun Liu:
Preparing Lessons for Progressive Training on Language Models. CoRR abs/2401.09192 (2024) - [i79]Yifang Qin, Wei Ju, Xiao Luo, Yiyang Gu, Zhiping Xiao, Ming Zhang:
PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering. CoRR abs/2401.12590 (2024) - [i78]Wei Ju, Yiyang Gu, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Xiao Luo, Hui Xiong, Ming Zhang:
GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling. CoRR abs/2401.16011 (2024) - [i77]Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Junyu Luo, Zhiping Xiao, Ming Zhang:
A Survey of Data-Efficient Graph Learning. CoRR abs/2402.00447 (2024) - [i76]Jianhao Shen, Ye Yuan, Srbuhi Mirzoyan, Ming Zhang, Chenguang Wang:
Measuring Vision-Language STEM Skills of Neural Models. CoRR abs/2402.17205 (2024) - [i75]Wei Ju, Yusheng Zhao, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, Ming Zhang:
COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting. CoRR abs/2403.01091 (2024) - [i74]Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang:
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges. CoRR abs/2403.04468 (2024) - [i73]Kangjie Zheng, Siyu Long, Tianyu Lu, Junwei Yang, Xinyu Dai, Ming Zhang, Zaiqing Nie, Wei-Ying Ma, Hao Zhou:
Multi-Scale Protein Language Model for Unified Molecular Modeling. CoRR abs/2403.12995 (2024) - [i72]Ye Yuan, Kexin Tang, Jianhao Shen, Ming Zhang, Chenguang Wang:
Measuring Social Norms of Large Language Models. CoRR abs/2404.02491 (2024) - [i71]Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, Ming Zhang:
Hypergraph-enhanced Dual Semi-supervised Graph Classification. CoRR abs/2405.04773 (2024) - [i70]Wei Ju, Yifan Wang, Yifang Qin, Zhengyang Mao, Zhiping Xiao, Junyu Luo, Junwei Yang, Yiyang Gu, Dongjie Wang, Qingqing Long, Siyu Yi, Xiao Luo, Ming Zhang:
Towards Graph Contrastive Learning: A Survey and Beyond. CoRR abs/2405.11868 (2024) - [i69]Jinsheng Huang, Liang Chen, Taian Guo, Fu Zeng, Yusheng Zhao, Bohan Wu, Ye Yuan, Haozhe Zhao, Zhihui Guo, Yichi Zhang, Jingyang Yuan, Wei Ju, Luchen Liu, Tianyu Liu, Baobao Chang, Ming Zhang:
MMEvalPro: Calibrating Multimodal Benchmarks Towards Trustworthy and Efficient Evaluation. CoRR abs/2407.00468 (2024) - [i68]Alan Wu, Ye Yuan, Ming Zhang:
Vision-Braille: An End-to-End Tool for Chinese Braille Image-to-Text Translation. CoRR abs/2407.06048 (2024) - [i67]Yifan Wang, Xiao Luo, Chong Chen, Xian-Sheng Hua, Ming Zhang, Wei Ju:
DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning. CoRR abs/2407.14081 (2024) - [i66]Ye Yuan, Chengwu Liu, Jingyang Yuan, Gongbo Sun, Siqi Li, Ming Zhang:
A Hybrid RAG System with Comprehensive Enhancement on Complex Reasoning. CoRR abs/2408.05141 (2024) - [i65]Bo-Wen Zhang, Liangdong Wang, Ye Yuan, Jijie Li, Shuhao Gu, Mengdi Zhao, Xinya Wu, Guang Liu, Chengwei Wu, Hanyu Zhao, Li Du, Yiming Ju, Quanyue Ma, Yulong Ao, Yingli Zhao, Songhe Zhu, Zhou Cao, Dong Liang, Yonghua Lin, Ming Zhang, Shunfei Wang, Yanxin Zhou, Min Ye, Xuekai Chen, Xinyang Yu, Xiangjun Huang, Jian Yang:
AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies. CoRR abs/2408.06567 (2024) - [i64]Junyu Luo, Zhiping Xiao, Yifan Wang, Xiao Luo, Jingyang Yuan, Wei Ju, Langechuan Liu, Ming Zhang:
Rank and Align: Towards Effective Source-free Graph Domain Adaptation. CoRR abs/2408.12185 (2024) - 2023
- [j24]Wei Ju, Yiyang Gu, Xiao Luo, Yifan Wang, Haochen Yuan, Huasong Zhong, Ming Zhang:
Unsupervised graph-level representation learning with hierarchical contrasts. Neural Networks 158: 359-368 (2023) - [j23]Wei Ju, Zequn Liu, Yifang Qin, Bin Feng, Chen Wang, Zhihui Guo, Xiao Luo, Ming Zhang:
Few-shot Molecular Property Prediction via Hierarchically Structured Learning on Relation Graphs. Neural Networks 163: 122-131 (2023) - [j22]Siyu Yi, Zhengyang Mao, Wei Ju, Yong-Dao Zhou, Luchen Liu, Xiao Luo, Ming Zhang:
Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts. IEEE Trans. Big Data 9(6): 1683-1696 (2023) - [j21]Xiao Luo, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun:
RIGNN: A Rationale Perspective for Semi-supervised Open-world Graph Classification. Trans. Mach. Learn. Res. 2023 (2023) - [j20]Wei Ju, Yifang Qin, Siyu Yi, Zhengyang Mao, Kangjie Zheng, Luchen Liu, Xiao Luo, Ming Zhang:
Zero-shot Node Classification with Graph Contrastive Embedding Network. Trans. Mach. Learn. Res. 2023 (2023) - [c159]Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang:
GLCC: A General Framework for Graph-Level Clustering. AAAI 2023: 4391-4399 - [c158]Zequn Liu, Wei Zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu:
MolXPT: Wrapping Molecules with Text for Generative Pre-training. ACL (2) 2023: 1606-1616 - [c157]Jing Xiong, Jianhao Shen, Ye Yuan, Haiming Wang, Yichun Yin, Zhengying Liu, Lin Li, Zhijiang Guo, Qingxing Cao, Yinya Huang, Chuanyang Zheng, Xiaodan Liang, Ming Zhang, Qun Liu:
TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models. EMNLP 2023: 11594-11632 - [c156]Jingyang Yuan, Xiao Luo, Yifang Qin, Yusheng Zhao, Wei Ju, Ming Zhang:
Learning on Graphs under Label Noise. ICASSP 2023: 1-5 - [c155]Kangjie Zheng, Longyue Wang, Zhihao Wang, Binqi Chen, Ming Zhang, Zhaopeng Tu:
Towards a Unified Training for Levenshtein Transformer. ICASSP 2023: 1-5 - [c154]Yusheng Zhao, Xiao Luo, Wei Ju, Chong Chen, Xian-Sheng Hua, Ming Zhang:
Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting. ICDE 2023: 2303-2316 - [c153]Xiao Luo, Jingyang Yuan, Zijie Huang, Huiyu Jiang, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun:
HOPE: High-order Graph ODE For Modeling Interacting Dynamics. ICML 2023: 23124-23139 - [c152]Jingyang Yuan, Xiao Luo, Yifang Qin, Zhengyang Mao, Wei Ju, Ming Zhang:
ALEX: Towards Effective Graph Transfer Learning with Noisy Labels. ACM Multimedia 2023: 3647-3656 - [c151]Zhengyang Mao, Wei Ju, Yifang Qin, Xiao Luo, Ming Zhang:
RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification. ACM Multimedia 2023: 3817-3826 - [c150]Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal A. C. Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang:
A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs. NeurIPS 2023 - [c149]Yifang Qin, Yifan Wang, Fang Sun, Wei Ju, Xuyang Hou, Zhe Wang, Jia Cheng, Jun Lei, Ming Zhang:
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation. WSDM 2023: 508-516 - [i63]Bin Feng, Tenglong Ao, Zequn Liu, Wei Ju, Libin Liu, Ming Zhang:
Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data. CoRR abs/2303.16856 (2023) - [i62]Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Xiao Luo, Ming Zhang:
A Comprehensive Survey on Deep Graph Representation Learning. CoRR abs/2304.05055 (2023) - [i61]Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang:
A Diffusion model for POI recommendation. CoRR abs/2304.07041 (2023) - [i60]Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo, Ming Zhang:
Learning Graph ODE for Continuous-Time Sequential Recommendation. CoRR abs/2304.07042 (2023) - [i59]Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
TGNN: A Joint Semi-supervised Framework for Graph-level Classification. CoRR abs/2304.11688 (2023) - [i58]Fang Sun, Zhihao Zhan, Hongyu Guo, Ming Zhang, Jian Tang:
GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow. CoRR abs/2304.12825 (2023) - [i57]Zequn Liu, Wei Zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu:
MolXPT: Wrapping Molecules with Text for Generative Pre-training. CoRR abs/2305.10688 (2023) - [i56]Xiao Luo, Yusheng Zhao, Yifang Qin, Wei Ju, Ming Zhang:
Towards Semi-supervised Universal Graph Classification. CoRR abs/2305.19598 (2023) - [i55]Jingyang Yuan, Xiao Luo, Yifang Qin, Yusheng Zhao, Wei Ju, Ming Zhang:
Learning on Graphs under Label Noise. CoRR abs/2306.08194 (2023) - [i54]Zhengyang Mao, Wei Ju, Yifang Qin, Xiao Luo, Ming Zhang:
RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification. CoRR abs/2308.02335 (2023) - [i53]Siyu Yi, Zhengyang Mao, Wei Ju, Yongdao Zhou, Luchen Liu, Xiao Luo, Ming Zhang:
Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts. CoRR abs/2308.16609 (2023) - [i52]Chengwu Liu, Jianhao Shen, Huajian Xin, Zhengying Liu, Ye Yuan, Haiming Wang, Wei Ju, Chuanyang Zheng, Yichun Yin, Lin Li, Ming Zhang, Qun Liu:
FIMO: A Challenge Formal Dataset for Automated Theorem Proving. CoRR abs/2309.04295 (2023) - [i51]Siyu Yi, Wei Ju, Yifang Qin, Xiao Luo, Luchen Liu, Yong-Dao Zhou, Ming Zhang:
Redundancy-Free Self-Supervised Relational Learning for Graph Clustering. CoRR abs/2309.04694 (2023) - [i50]Yusheng Zhao, Xiao Luo, Wei Ju, Chong Chen, Xian-Sheng Hua, Ming Zhang:
Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting. CoRR abs/2309.12028 (2023) - [i49]Jingyang Yuan, Xiao Luo, Yifang Qin, Zhengyang Mao, Wei Ju, Ming Zhang:
ALEX: Towards Effective Graph Transfer Learning with Noisy Labels. CoRR abs/2309.14673 (2023) - [i48]Jing Xiong, Jianhao Shen, Ye Yuan, Haiming Wang, Yichun Yin, Zhengying Liu, Lin Li, Zhijiang Guo, Qingxing Cao, Yinya Huang, Chuanyang Zheng, Xiaodan Liang, Ming Zhang, Qun Liu:
TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models. CoRR abs/2310.10180 (2023) - [i47]Xiao Luo, Yiyang Gu, Huiyu Jiang, Jinsheng Huang, Wei Ju, Ming Zhang, Yizhou Sun:
Graph ODE with Factorized Prototypes for Modeling Complicated Interacting Dynamics. CoRR abs/2311.06554 (2023) - [i46]Jiankai Sun, Chuanyang Zheng, Enze Xie, Zhengying Liu, Ruihang Chu, Jianing Qiu, Jiaqi Xu, Mingyu Ding, Hongyang Li, Mengzhe Geng, Yue Wu, Wenhai Wang, Junsong Chen, Zhangyue Yin, Xiaozhe Ren, Jie Fu, Junxian He, Wu Yuan, Qi Liu, Xihui Liu, Yu Li, Hao Dong, Yu Cheng, Ming Zhang, Pheng-Ann Heng, Jifeng Dai, Ping Luo, Jingdong Wang, Ji-Rong Wen, Xipeng Qiu, Yike Guo, Hui Xiong, Qun Liu, Zhenguo Li:
A Survey of Reasoning with Foundation Models. CoRR abs/2312.11562 (2023) - 2022
- [j19]Ruiyi Zhang, Yunan Luo, Jianzhu Ma, Ming Zhang, Sheng Wang:
scPretrain: multi-task self-supervised learning for cell-type classification. Bioinform. 38(6): 1607-1614 (2022) - [j18]Wei Ju, Xiao Luo, Zeyu Ma, Junwei Yang, Minghua Deng, Ming Zhang:
GHNN: Graph Harmonic Neural Networks for semi-supervised graph-level classification. Neural Networks 151: 70-79 (2022) - [c148]Yifan Wang, Yiping Song, Shuai Li, Chaoran Cheng, Wei Ju, Ming Zhang, Sheng Wang:
DisenCite: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation. AAAI 2022: 11449-11458 - [c147]Yifan Wang, Yongkang Li, Shuai Li, Weiping Song, Jiangke Fan, Shan Gao, Ling Ma, Bing Cheng, Xunliang Cai, Sheng Wang, Ming Zhang:
Deep Graph Mutual Learning for Cross-domain Recommendation. DASFAA (2) 2022: 298-305 - [c146]Jianhao Shen, Chenguang Wang, Ye Yuan, Jiawei Han, Heng Ji, Koushik Sen, Ming Zhang, Dawn Song:
PALT: Parameter-Lite Transfer of Language Models for Knowledge Graph Completion. EMNLP (Findings) 2022: 3833-3847 - [c145]Zequn Liu, Kefei Duan, Junwei Yang, Hanwen Xu, Ming Zhang, Sheng Wang:
MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks. EMNLP 2022: 5110-5122 - [c144]Yiping Song, Zheng Xie, Jianping Li, Luchen Liu, Ming Zhang, Zhiliang Tian:
Retrieval Bias Aware Ensemble Model for Conditional Sentence Generation. ICASSP 2022: 6602-6606 - [c143]Xiao Luo, Wei Ju, Meng Qu, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
DualGraph: Improving Semi-supervised Graph Classification via Dual Contrastive Learning. ICDE 2022: 699-712 - [c142]Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang:
Kernel-based Substructure Exploration for Next POI Recommendation. ICDM 2022: 221-230 - [c141]Yiping Song, Wei Ju, Zhiliang Tian, Luchen Liu, Ming Zhang, Zheng Xie:
Building Conversational Diagnosis Systems for Fine-Grained Diseases Using Few Annotated Data. ICONIP (3) 2022: 591-603 - [c140]Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
TGNN: A Joint Semi-supervised Framework for Graph-level Classification. IJCAI 2022: 2122-2128 - [c139]Yifan Wang, Jianhao Shen, Yiping Song, Sheng Wang, Ming Zhang:
HE-SNE: Heterogeneous Event Sequence-based Streaming Network Embedding for Dynamic Behaviors. IJCNN 2022: 1-8 - [c138]Junwei Yang, Zequn Liu, Ming Zhang, Sheng Wang:
Pathway2Text: Dataset and Method for Biomedical Pathway Description Generation. NAACL-HLT (Findings) 2022: 1441-1454 - [c137]Yifan Wang, Yifang Qin, Yu Han, Mingyang Yin, Jingren Zhou, Hongxia Yang, Ming Zhang:
AD-AUG: Adversarial Data Augmentation for Counterfactual Recommendation. ECML/PKDD (1) 2022: 474-490 - [c136]Yifan Wang, Yifang Qin, Fang Sun, Bo Zhang, Xuyang Hou, Ke Hu, Jia Cheng, Jun Lei, Ming Zhang:
DisenCTR: Dynamic Graph-based Disentangled Representation for Click-Through Rate Prediction. SIGIR 2022: 2314-2318 - [c135]Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang:
KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification. WSDM 2022: 421-429 - [i45]Gongbo Sun, Zijie Zheng, Ming Zhang:
End-to-End Rubbing Restoration Using Generative Adversarial Networks. CoRR abs/2205.03743 (2022) - [i44]Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang:
KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification. CoRR abs/2205.10550 (2022) - [i43]Zhaocheng Zhu, Xinyu Yuan, Louis-Pascal A. C. Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang:
Learning to Efficiently Propagate for Reasoning on Knowledge Graphs. CoRR abs/2206.04798 (2022) - [i42]Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang:
Kernel-based Substructure Exploration for Next POI Recommendation. CoRR abs/2210.03969 (2022) - [i41]Zequn Liu, Kefei Duan, Junwei Yang, Hanwen Xu, Ming Zhang, Sheng Wang:
MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks. CoRR abs/2210.07488 (2022) - [i40]Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang:
GLCC: A General Framework for Graph-level Clustering. CoRR abs/2210.11879 (2022) - [i39]Jianhao Shen, Chenguang Wang, Ye Yuan, Jiawei Han, Heng Ji, Koushik Sen, Ming Zhang, Dawn Song:
PALT: Parameter-Lite Transfer of Language Models for Knowledge Graph Completion. CoRR abs/2210.13715 (2022) - [i38]Yifang Qin, Yifan Wang, Fang Sun, Wei Ju, Xuyang Hou, Zhe Wang, Jia Cheng, Jun Lei, Ming Zhang:
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation. CoRR abs/2210.16591 (2022) - [i37]Yongkang Li, Ming Zhang:
TIER-A: Denoising Learning Framework for Information Extraction. CoRR abs/2211.11527 (2022) - 2021
- [c134]Jianhao Shen, Yichun Yin, Lin Li, Lifeng Shang, Xin Jiang, Ming Zhang, Qun Liu:
Generate & Rank: A Multi-task Framework for Math Word Problems. EMNLP (Findings) 2021: 2269-2279 - [c133]Zequn Liu, Shukai Wang, Yiyang Gu, Ruiyi Zhang, Ming Zhang, Sheng Wang:
Graphine: A Dataset for Graph-aware Terminology Definition Generation. EMNLP (1) 2021: 3453-3463 - [c132]Kewei Cheng, Ziqing Yang, Ming Zhang, Yizhou Sun:
UniKER: A Unified Framework for Combining Embedding and Definite Horn Rule Reasoning for Knowledge Graph Inference. EMNLP (1) 2021: 9753-9771 - [i36]Yifan Wang, Suyao Tang, Yuntong Lei, Weiping Song, Sheng Wang, Ming Zhang:
DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation. CoRR abs/2106.10879 (2021) - [i35]Jianhao Shen, Yichun Yin, Lin Li, Lifeng Shang, Xin Jiang, Ming Zhang, Qun Liu:
Generate & Rank: A Multi-task Framework for Math Word Problems. CoRR abs/2109.03034 (2021) - [i34]Zequn Liu, Shukai Wang, Yiyang Gu, Ruiyi Zhang, Ming Zhang, Sheng Wang:
Graphine: A Dataset for Graph-aware Terminology Definition Generation. CoRR abs/2109.04018 (2021) - 2020
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Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks. ACL 2020: 5832-5841 - [c130]Luchen Liu, Zequn Liu, Haoxian Wu, Zichang Wang, Jianhao Shen, Yiping Song, Ming Zhang:
Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases. AMIA 2020 - [c129]