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ORCIDMing Zhang 0004
Person information
- affiliation: 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.dagstuhl.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
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2020 – today
- 2023
[j20]Wei Ju, Yiyang Gu, Xiao Luo, Yi-Fan Wang, Haochen Yuan, Huasong Zhong, Ming Zhang:
Unsupervised graph-level representation learning with hierarchical contrasts. Neural Networks 158: 359-368 (2023)- [c146]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 - [i51]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) - [i50]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) - [i49]Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang:
A Diffusion model for POI recommendation. CoRR abs/2304.07041 (2023) - [i48]Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo, Ming Zhang:
Learning Graph ODE for Continuous-Time Sequential Recommendation. CoRR abs/2304.07042 (2023) - [i47]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) - [i46]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) - 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) - [c145]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 - [c144]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 - [c143]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 - [c142]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 - [c141]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 - [c140]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 - [c139]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 - [c138]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 - [c137]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 - [c136]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 - [c135]Junwei Yang, Zequn Liu, Ming Zhang, Sheng Wang:
Pathway2Text: Dataset and Method for Biomedical Pathway Description Generation. NAACL-HLT (Findings) 2022: 1441-1454 - [c134]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 - [c133]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 - [c132]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
- [c131]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 - [c130]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 - [c129]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
- [c128]Yiping Song, Zequn Liu, Wei Bi, Rui Yan, Ming Zhang:
Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks. ACL 2020: 5832-5841 - [c127]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 - [c126]Yifan Wang, Suyao Tang, Yuntong Lei, Weiping Song, Sheng Wang, Ming Zhang:
DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation. CIKM 2020: 1605-1614 - [c125]Yichun Yin, Chenguang Wang, Ming Zhang:
PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction. COLING 2020: 1714-1719 - [c124]Ming Zhang, Shixing Liu, Yifan Wang:
STR-SA: Session-based Thread Recommendation for Online Course Forum with Self-Attention. EDUCON 2020: 374-381 - [c123]Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang:
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation. ICLR 2020 - [c122]Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang:
A Graph to Graphs Framework for Retrosynthesis Prediction. ICML 2020: 8818-8827 - [c121]Baoming Yan, Chen Zhou, Bo Zhao, Kan Guo, Jiang Yang, Xiaobo Li, Ming Zhang, Yizhou Wang:
Augmented Bi-path Network for Few-shot Learning. ICPR 2020: 8461-8468 - [c120]Jiafa He, Chengwei Pan, Can Yang, Ming Zhang, Yang Wang, Xiaowei Zhou, Yizhou Yu:
Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction. MICCAI (6) 2020: 24-34 - [c119]Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu:
Multi-agent Trajectory Prediction with Fuzzy Query Attention. NeurIPS 2020 - [i33]Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang:
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation. CoRR abs/2001.09382 (2020) - [i32]Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang:
A Graph to Graphs Framework for Retrosynthesis Prediction. CoRR abs/2003.12725 (2020) - [i31]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. CoRR abs/2004.05318 (2020) - [i30]Zequn Liu, Ruiyi Zhang, Yiping Song, Ming Zhang:
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications. CoRR abs/2005.11700 (2020) - [i29]Baoming Yan, Chen Zhou, Bo Zhao, Kan Guo, Jiang Yang, Xiaobo Li, Ming Zhang, Yizhou Wang:
Augmented Bi-path Network for Few-shot Learning. CoRR abs/2007.07614 (2020) - [i28]Yicheng Wu, Chengwei Pan, Shuqi Wang, Ming Zhang, Yong Xia, Yizhou Yu:
Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation. CoRR abs/2010.04428 (2020) - [i27]Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu:
Multi-agent Trajectory Prediction with Fuzzy Query Attention. CoRR abs/2010.15891 (2020) - [i26]Jiafa He, Chengwei Pan, Can Yang, Ming Zhang, Yang Wang, Xiaowei Zhou, Yizhou Yu:
Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction. CoRR abs/2012.07262 (2020)
2010 – 2019
- 2019
- [j17]Ming Zhang, Stephen Cooper, Andrew Luxton-Reilly:
Report on the First ACM Global Computing Education Conference (CompEd). ACM SIGCSE Bull. 51(3): 4-6 (2019) - [j16]Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu:
Combating Fake News: A Survey on Identification and Mitigation Techniques. ACM Trans. Intell. Syst. Technol. 10(3): 21:1-21:42 (2019) - [j15]Ming Zhang, Jile Zhu, Zhuo Wang, Yunfan Chen:
Providing personalized learning guidance in MOOCs by multi-source data analysis. World Wide Web 22(3): 1189-1219 (2019) - [c118]Ming Zhang, Yichun Yin:
More Chinese women needed to hold up half the computing sky. ACM TUR-C 2019: 69:1-69:4 - [c117]Luchen Liu, Haoran Li, Zhiting Hu, Haoran Shi, Zichang Wang, Jian Tang, Ming Zhang:
Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction. AMIA 2019 - [c116]Zichang Wang, Haoran Li, Luchen Liu, Haoxian Wu, Ming Zhang:
Predictive Multi-level Patient Representations from Electronic Health Records. BIBM 2019: 987-990 - [c115]Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, Jian Tang:
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks. CIKM 2019: 1161-1170 - [c114]Luchen Liu, Haoxian Wu, Zichang Wang, Zequn Liu, Ming Zhang:
Early Prediction of Sepsis From Clinical Data via Heterogeneous Event Aggregation. CinC 2019: 1-4 - [c113]Jingyu Liu, Gangming Zhao, Yu Fei, Ming Zhang, Yizhou Wang, Yizhou Yu:
Align, Attend and Locate: Chest X-Ray Diagnosis via Contrast Induced Attention Network With Limited Supervision. ICCV 2019: 10631-10640 - [c112]Alison Clear, Allen S. Parrish, John Impagliazzo, Ming Zhang:
Computing Curricula 2020: Introduction and Community Engagement. SIGCSE 2019: 653-654 - [c111]Alison Clear, John Impagliazzo, Ming Zhang:
Computing Competencies and the CC2020 Project. SIGCSE 2019: 1245-1246 - [c110]Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang:
Session-Based Social Recommendation via Dynamic Graph Attention Networks. WSDM 2019: 555-563 - [e1]Ming Zhang, Bo Yang, Steve Cooper, Andrew Luxton-Reilly:
Proceedings of the ACM Conference on Global Computing Education, CompEd 2019, Chengdu,Sichuan, China, May 17-19, 2019. ACM 2019, ISBN 978-1-4503-6259-7 [contents] - [i25]Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu:
Combating Fake News: A Survey on Identification and Mitigation Techniques. CoRR abs/1901.06437 (2019) - [i24]Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang:
Session-based Social Recommendation via Dynamic Graph Attention Networks. CoRR abs/1902.09362 (2019) - [i23]Luchen Liu, Haoran Li, Zhiting Hu, Haoran Shi, Zichang Wang, Jian Tang, Ming Zhang:
Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction. CoRR abs/1903.08652 (2019) - [i22]Weiping Song, Zhijian Duan, Ziqing Yang, Hao Zhu, Ming Zhang, Jian Tang:
Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning. CoRR abs/1906.09506 (2019) - [i21]Mengdi Zhu, Zheye Deng, Wenhan Xiong, Mo Yu, Ming Zhang, William Yang Wang:
Towards Open-Domain Named Entity Recognition via Neural Correction Models. CoRR abs/1909.06058 (2019) - [i20]Luchen Liu, Haoxian Wu, Zichang Wang, Zequn Liu, Ming Zhang:
Early Prediction of Sepsis From Clinical Datavia Heterogeneous Event Aggregation. CoRR abs/1910.06792 (2019) - [i19]Yiping Song, Zequn Liu, Wei Bi, Rui Yan, Ming Zhang:
Learning to Customize Language Model for Generation-based dialog systems. CoRR abs/1910.14326 (2019) - [i18]Yichun Yin, Chenguang Wang, Ming Zhang:
PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction. CoRR abs/1911.03785 (2019) - [i17]Zichang Wang, Haoran Li, Luchen Liu, Haoxian Wu, Ming Zhang:
Predictive Multi-level Patient Representations from Electronic Health Records. CoRR abs/1911.05698 (2019) - [i16]Yikai Zhu, Jianhao Shen, Ming Zhang:
Learning to Answer Ambiguous Questions with Knowledge Graph. CoRR abs/1912.11668 (2019) - 2018
- [j14]Chenguang Wang, Yangqiu Song, Haoran Li, Ming Zhang, Jiawei Han:
Unsupervised meta-path selection for text similarity measure based on heterogeneous information networks. Data Min. Knowl. Discov. 32(6): 1735-1767 (2018) - [j13]John Impagliazzo, Ming Zhang, Xi Wu:
SIGCSE launches new conference on a global scale. ACM SIGCSE Bull. 50(4): 2-3 (2018) - [c109]Luchen Liu, Jianhao Shen, Ming Zhang, Zichang Wang, Jian Tang:
Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction. AAAI 2018: 109-116 - [c108]Yiping Song, Rui Yan, Yansong Feng, Yaoyuan Zhang, Dongyan Zhao, Ming Zhang:
Towards a Neural Conversation Model With Diversity Net Using Determinantal Point Processes. AAAI 2018: 5932-5939 - [c107]Pengtao Xie, Haoran Shi, Ming Zhang, Eric P. Xing:
A Neural Architecture for Automated ICD Coding. ACL (1) 2018: 1066-1076 - [c106]Xiang Li, Ming Zhang:
Emotion Analysis for the Upcoming Response in Open-Domain Human-Computer Conversation. APWeb/WAIM Workshops 2018: 352-367 - [c105]Yiping Song, Cheng-Te Li, Jian-Yun Nie, Ming Zhang, Dongyan Zhao, Rui Yan:
An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems. IJCAI 2018: 4382-4388 - [c104]Mihaela Sabin, John Impagliazzo, Hala Alrumaih, Cara Tang, Ming Zhang:
IT2017 Report: Implementing A Competency-Based Information Technology Program. SIGCSE 2018: 1045-1046 - [c103]Barbara Boucher Owens, Alison Clear, John Impagliazzo, Mirella M. Moro, Ming Zhang:
Global Awareness for Computing Educators and Scholars: (Abstract Only). SIGCSE 2018: 1069 - [i15]Luchen Liu, Jianhao Shen, Ming Zhang, Zichang Wang, Jian Tang:
Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction. CoRR abs/1803.04837 (2018) - [i14]Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, Jian Tang:
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks. CoRR abs/1810.11921 (2018) - 2017
- [c102]Ming Zhang, Jile Zhu:
A data-driven analysis of student efforts and improvements on a SPOC experiment. ACM TUR-C 2017: 1:1-1:6 - [c101]Yunfan Chen, Ming Zhang:
MOOC student dropout: pattern and prevention. ACM TUR-C 2017: 4:1-4:6 - [c100]Yao Guo, Junlin Lu, Yifeng Chen, Ming Zhang, Wenxin Li:
Hybrid small class teaching: dividing and conquering large computer systems classes. ACM TUR-C 2017: 5:1-5:6 - [c99]Xiang Li, Rui Yan, Ming Zhang:
Joint Emoji Classification and Embedding Learning. APWeb/WAIM (2) 2017: 48-63 - [c98]Feng Qian, ChengYue Gong, Lu-chen Liu, Lei Sha, Ming Zhang:
Topic medical concept embedding: Multi-sense representation learning for medical concept. BIBM 2017: 404-409 - [c97]Chenguang Wang, Yangqiu Song, Haoran Li, Yizhou Sun, Ming Zhang, Jiawei Han:
Distant Meta-Path Similarities for Text-Based Heterogeneous Information Networks. CIKM 2017: 1629-1638 - [c96]Meng Qu, Jian Tang, Jingbo Shang, Xiang Ren, Ming Zhang, Jiawei Han:
An Attention-based Collaboration Framework for Multi-View Network Representation Learning. CIKM 2017: 1767-1776 - [c95]Jile Zhu, Xiang Li, Zhuo Wang, Ming Zhang:
An Effective Framework for Automatically Generating and Ranking Topics in MOOC Videos. EDM 2017 - [c94]Feng Qian, Lei Sha, Baobao Chang, Lu-chen Liu, Ming Zhang:
Syntax Aware LSTM model for Semantic Role Labeling. SPNLP@EMNLP 2017: 27-32 - [c93]Yichun Yin, Yangqiu Song, Ming Zhang:
Document-Level Multi-Aspect Sentiment Classification as Machine Comprehension. EMNLP 2017: 2044-2054 - [c92]He Jiang, Yangqiu Song, Chenguang Wang, Ming Zhang, Yizhou Sun:
Semi-supervised Learning over Heterogeneous Information Networks by Ensemble of Meta-graph Guided Random Walks. IJCAI 2017: 1944-1950 - [c91]Ziqian Zeng, Yichun Yin, Yangqiu Song, Ming Zhang:
Socialized Word Embeddings. IJCAI 2017: 3915-3921 - [c90]Yiping Song, Zhiliang Tian, Dongyan Zhao, Ming Zhang, Rui Yan:
Diversifying Neural Conversation Model with Maximal Marginal Relevance. IJCNLP(2) 2017: 169-174 - [c89]Yichun Yin, Yangqiu Song, Ming Zhang:
NNEMBs at SemEval-2017 Task 4: Neural Twitter Sentiment Classification: a Simple Ensemble Method with Different Embeddings. SemEval@ACL 2017: 621-625 - [c88]Alison Clear, Allen Parrish, Ming Zhang, Gerrit C. van der Veer:
CC2020: A Vision on Computing Curricula. SIGCSE 2017: 647-648 - [c87]Mihaela Sabin, Svetlana Peltsverger, Bill Paterson, Ming Zhang, Hala Alrumaih:
IT2017 Report: Putting It to Work. SIGITE 2017: 95-96 - [i13]Feng Qian, Lei Sha, Baobao Chang, Lu-chen Liu, Ming Zhang:
Syntax Aware LSTM Model for Chinese Semantic Role Labeling. CoRR abs/1704.00405 (2017) - [i12]Meng Qu, Jian Tang, Jingbo Shang, Xiang Ren, Ming Zhang, Jiawei Han:
An Attention-based Collaboration Framework for Multi-View Network Representation Learning. CoRR abs/1709.06636 (2017) - [i11]Haoran Shi, Pengtao Xie, Zhiting Hu, Ming Zhang, Eric P. Xing:
Towards Automated ICD Coding Using Deep Learning. CoRR abs/1711.04075 (2017) - 2016
- [j12]John Impagliazzo, Yan Timanovsky, Ming Zhang:
EduBits. Inroads 7(1): 14-16 (2016) - [j11]Chenguang Wang, Yangqiu Song, Dan Roth, Ming Zhang, Jiawei Han:
World Knowledge as Indirect Supervision for Document Clustering. ACM Trans. Knowl. Discov. Data 11(2): 13:1-13:36 (2016) - [c86]Chenguang Wang, Yangqiu Song, Haoran Li, Ming Zhang, Jiawei Han:
Text Classification with Heterogeneous Information Network Kernels. AAAI 2016: 2130-2136 - [c85]Rui Yan, Cheng-Te Li, Xiaohua Hu, Ming Zhang:
Chinese Couplet Generation with Neural Network Structures. ACL (1) 2016 - [c84]