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- affiliation: University of Michigan, Ann Arbor, USA
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2020 – today
- 2023
[i43]Xuan Lu, Wei Ai, Yixin Wang, Qiaozhu Mei:
Team Resilience under Shock: An Empirical Analysis of GitHub Repositories during Early COVID-19 Pandemic. CoRR abs/2301.12326 (2023)- [i42]Yutong Xie, Zhaoying Pan, Jinge Ma, Luo Jie, Qiaozhu Mei:
A Prompt Log Analysis of Text-to-Image Generation Systems. CoRR abs/2303.04587 (2023) - 2022
- [j29]Weijing Tang, Jiaqi Ma, Qiaozhu Mei, Ji Zhu:
SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks. J. Mach. Learn. Res. 23: 34:1-34:29 (2022) - [j28]Huoran Li, Fuqi Lin
, Xuan Lu, Chenren Xu, Gang Huang, Jun Zhang, Qiaozhu Mei, Xuanzhe Liu:
Systematic Analysis of Fine-Grained Mobility Prediction With On-Device Contextual Data. IEEE Trans. Mob. Comput. 21(3): 1096-1109 (2022) - [c117]Cristina Garbacea, Qiaozhu Mei:
Adapting Pre-trained Language Models to Low-Resource Text Simplification: The Path Matters. CoLLAs 2022: 1103-1119 - [c116]Jiaqi Ma, Xingjian Zhang, Hezheng Fan, Jin Huang, Tianyue Li, Ting Wei Li, Yiwen Tu, Chenshu Zhu, Qiaozhu Mei:
Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks. LoG 2022: 7 - [c115]Jiaqi Ma, Junwei Deng, Qiaozhu Mei:
Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem. WSDM 2022: 675-685 - [c114]Jiaqi Ma, Xingjian Zhang, Qiaozhu Mei:
Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling. WSDM 2022: 715-725 - [i41]Jiaqi Ma, Ziqiao Ma, Joyce Chai, Qiaozhu Mei:
Partition-Based Active Learning for Graph Neural Networks. CoRR abs/2201.09391 (2022) - [i40]Cristina Garbacea, Qiaozhu Mei:
Why is constrained neural language generation particularly challenging? CoRR abs/2206.05395 (2022) - [i39]Jiaqi Ma, Xingjian Zhang, Hezheng Fan, Jin Huang, Tianyue Li, Ting Wei Li, Yiwen Tu, Chenshu Zhu, Qiaozhu Mei:
Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks. CoRR abs/2212.04537 (2022) - 2021
- [j27]Xuedong Li, Walter Yuan, Dezhong Peng, Qiaozhu Mei, Yue Wang:
When BERT meets Bilbo: a learning curve analysis of pretrained language model on disease classification. BMC Medical Informatics Decis. Mak. 21-S(9): 377 (2021) - [j26]Xuanzhe Liu, Shangguang Wang, Yun Ma, Ying Zhang, Qiaozhu Mei, Yunxin Liu, Gang Huang:
Operating Systems for Resource-adaptive Intelligent Software: Challenges and Opportunities. ACM Trans. Internet Techn. 21(2): 27:1-27:19 (2021) - [c113]Cristina Garbacea, Mengtian Guo, Samuel Carton, Qiaozhu Mei:
Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification. ACL/IJCNLP (1) 2021: 1086-1097 - [c112]Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei:
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. AISTATS 2021: 928-936 - [c111]Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei:
CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks. ICLR 2021 - [c110]Jiaqi Ma, Junwei Deng, Qiaozhu Mei:
Subgroup Generalization and Fairness of Graph Neural Networks. NeurIPS 2021: 1048-1061 - [c109]Jialiang Han, Yun Ma, Qiaozhu Mei, Xuanzhe Liu:
DeepRec: On-device Deep Learning for Privacy-Preserving Sequential Recommendation in Mobile Commerce. WWW 2021: 900-911 - [i38]Xuan Lu, Wei Ai, Zhenpeng Chen, Yanbin Cao, Xuanzhe Liu, Qiaozhu Mei:
Emojis Predict Dropouts of Remote Workers: An Empirical Study of Emoji Usage on GitHub. CoRR abs/2102.05737 (2021) - [i37]Jiaqi Ma, Junwei Deng, Qiaozhu Mei:
Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem. CoRR abs/2106.10785 (2021) - [i36]Jiaqi Ma, Junwei Deng, Qiaozhu Mei:
Subgroup Generalization and Fairness of Graph Neural Networks. CoRR abs/2106.15535 (2021) - [i35]Yutong Xie, Ziqiao Xu, Jiaqi Ma, Qiaozhu Mei:
How Much of the Chemical Space Has Been Covered? Measuring and Improving the Variety of Candidate Set in Molecular Generation. CoRR abs/2112.12542 (2021) - [i34]Jiaqi Ma, Xingjian Zhang, Qiaozhu Mei:
Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling. CoRR abs/2112.15575 (2021) - 2020
- [j25]Yun Ma, Ziniu Hu, Diandian Gu, Li Zhou, Qiaozhu Mei, Gang Huang, Xuanzhe Liu:
Roaming Through the Castle Tunnels: An Empirical Analysis of Inter-app Navigation of Android Apps. ACM Trans. Web 14(3): 14:1-14:24 (2020) - [c108]Jiazhao Li, Adharsh Murali, Qiaozhu Mei, V. G. Vinod Vydiswaran:
Re-ranking Biomedical Literature for Precision Medicine with Pre-trained Neural Models. ICHI 2020: 1-3 - [c107]Xuedong Li, Walter Yuan, Dezhong Peng, Qiaozhu Mei, Yue Wang:
When BERT Meets Bilbo: A Learning Curve Analysis of Pretrained Language Model on Disease Classification. ICHI 2020: 1-2 - [c106]Qiang Wei, Yujia Zhou, Bo Zhao, Xinyue Hu, Qiaozhu Mei, Cui Tao, Hua Xu:
Named Entity Recognition from Table Headers in Randomized Controlled Trial Articles. ICHI 2020: 1-2 - [c105]Samuel Carton, Qiaozhu Mei, Paul Resnick:
Feature-Based Explanations Don't Help People Detect Misclassifications of Online Toxicity. ICWSM 2020: 95-106 - [c104]Zhenpeng Chen, Sheng Shen, Ziniu Hu, Xuan Lu, Qiaozhu Mei, Xuanzhe Liu:
Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification (Extended Abstract). IJCAI 2020: 4701-4705 - [c103]Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, Qiaozhu Mei:
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy. KDD 2020: 2368-2377 - [c102]Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei:
Towards More Practical Adversarial Attacks on Graph Neural Networks. NeurIPS 2020 - [c101]Yunzhe Jiang, Cristina Garbacea, Qiaozhu Mei:
UMSIForeseer at SemEval-2020 Task 11: Propaganda Detection by Fine-Tuning BERT with Resampling and Ensemble Learning. SemEval@COLING 2020: 1841-1846 - [i33]Mengwei Xu, Yuxin Zhao, Kaigui Bian, Gang Huang, Qiaozhu Mei, Xuanzhe Liu:
Neural Architecture Search over Decentralized Data. CoRR abs/2002.06352 (2020) - [i32]Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei:
Black-Box Adversarial Attacks on Graph Neural Networks with Limited Node Access. CoRR abs/2006.05057 (2020) - [i31]Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei:
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. CoRR abs/2006.05067 (2020) - [i30]Cristina Garbacea, Qiaozhu Mei:
Neural Language Generation: Formulation, Methods, and Evaluation. CoRR abs/2007.15780 (2020) - [i29]Cristina Garbacea, Mengtian Guo, Samuel Carton, Qiaozhu Mei:
An Empirical Study on Explainable Prediction of Text Complexity: Preliminaries for Text Simplification. CoRR abs/2007.15823 (2020) - [i28]Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, Qiaozhu Mei:
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy. CoRR abs/2008.07364 (2020) - [i27]Weijing Tang, Jiaqi Ma, Qiaozhu Mei, Ji Zhu:
SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks. CoRR abs/2008.08637 (2020) - [i26]Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei:
CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks. CoRR abs/2010.02089 (2020)
2010 – 2019
- 2019
- [j24]Qiang Wei, Yukun Chen, Mandana Salimi, Joshua C. Denny, Qiaozhu Mei, Thomas A. Lasko, Qingxia Chen, Stephen Wu, Amy Franklin, Trevor Cohen, Hua Xu:
Cost-aware active learning for named entity recognition in clinical text. J. Am. Medical Informatics Assoc. 26(11): 1314-1322 (2019) - [j23]David A. Hanauer, Qiaozhu Mei, V. G. Vinod Vydiswaran, Karandeep Singh, Zach Landis-Lewis, Chunhua Weng:
Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification. BMC Medical Informatics Decis. Mak. 19-S(3): 59-69 (2019) - [j22]Xuedong Li, Yue Wang, Dongwu Wang, Walter Yuan, Dezhong Peng, Qiaozhu Mei:
Improving rare disease classification using imperfect knowledge graph. BMC Medical Informatics Decis. Mak. 19-S(5): 9 (2019) - [c100]Cristina Garbacea, Samuel Carton, Shiyan Yan, Qiaozhu Mei:
Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation. EMNLP/IJCNLP (1) 2019: 3966-3979 - [c99]Xuedong Li, Yue Wang, Dongwu Wang, Walter Yuan, Dezhong Peng, Qiaozhu Mei:
Improving Rare Disease Classification Using Imperfect Knowledge Graph. ICHI 2019: 1-2 - [c98]Kai Zheng, Yunan Chen, Julia Adler-Milstein, Andrew L. Rosenberg, Danny T. Y. Wu, Qiaozhu Mei, David A. Hanauer:
How Do Healthcare Professionals Personalize Their Software? A Pilot Exploration Based on an Electronic Health Records Search Engine. MedInfo 2019: 1408-1412 - [c97]Jiatong Li, Kai Zheng, Hua Xu, Qiaozhu Mei, Yue Wang:
The Strength of the Weakest Supervision: Topic Classification Using Class Labels. NAACL-HLT (Student Research Workshop) 2019: 22-28 - [c96]Jiaqi Ma, Weijing Tang, Ji Zhu, Qiaozhu Mei:
A Flexible Generative Framework for Graph-based Semi-supervised Learning. NeurIPS 2019: 3276-3285 - [c95]Zhenpeng Chen, Yanbin Cao, Xuan Lu, Qiaozhu Mei, Xuanzhe Liu:
SEntiMoji: an emoji-powered learning approach for sentiment analysis in software engineering. ESEC/SIGSOFT FSE 2019: 841-852 - [c94]Zhenpeng Chen, Sheng Shen, Ziniu Hu, Xuan Lu, Qiaozhu Mei, Xuanzhe Liu:
Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification. WWW 2019: 251-262 - [c93]Qiaozhu Mei:
Decoding the New World Language: Analyzing the Popularity, Roles, and Utility of Emojis. WWW (Companion Volume) 2019: 417-418 - [i25]Cristina Garbacea, Samuel Carton, Shiyan Yan, Qiaozhu Mei:
Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation. CoRR abs/1901.00398 (2019) - [i24]Jiaqi Ma, Weijing Tang, Ji Zhu, Qiaozhu Mei:
A Flexible Generative Framework for Graph-based Semi-supervised Learning. CoRR abs/1905.10769 (2019) - [i23]Zhenpeng Chen, Yanbin Cao, Xuan Lu, Qiaozhu Mei, Xuanzhe Liu:
SEntiMoji: An Emoji-Powered Learning Approach for Sentiment Analysis in Software Engineering. CoRR abs/1907.02202 (2019) - [i22]Jiaqi Ma, Qiaozhu Mei:
Graph Representation Learning via Multi-task Knowledge Distillation. CoRR abs/1911.05700 (2019) - 2018
- [j21]Mengwei Xu, Feng Qian, Qiaozhu Mei, Kang Huang, Xuanzhe Liu:
DeepType: On-Device Deep Learning for Input Personalization Service with Minimal Privacy Concern. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2(4): 197:1-197:26 (2018) - [j20]Yue Wang, Kai Zheng, Hua Xu, Qiaozhu Mei:
Interactive medical word sense disambiguation through informed learning. J. Am. Medical Informatics Assoc. 25(7): 800-808 (2018) - [j19]Xuanzhe Liu, Huoran Li, Xuan Lu, Tao Xie, Qiaozhu Mei, Feng Feng, Hong Mei:
Understanding Diverse Usage Patterns from Large-Scale Appstore-Service Profiles. IEEE Trans. Software Eng. 44(4): 384-411 (2018) - [j18]Yue Wang, Dawei Yin, Luo Jie, Pengyuan Wang, Makoto Yamada, Yi Chang, Qiaozhu Mei:
Optimizing Whole-Page Presentation for Web Search. ACM Trans. Web 12(3): 19:1-19:25 (2018) - [c92]Huoran Li, Xuanzhe Liu, Hong Mei, Qiaozhu Mei:
Mining Device-Specific Apps Usage Patterns from Appstore Big Data. Big Data (CCF) 2018: 55-76 - [c91]Shan Jiang, Chengxiang Zhai, Qiaozhu Mei:
Exploiting Knowledge Graph to Improve Text-based Prediction. IEEE BigData 2018: 1407-1416 - [c90]Samuel Carton, Qiaozhu Mei, Paul Resnick:
Extractive Adversarial Networks: High-Recall Explanations for Identifying Personal Attacks in Social Media Posts. EMNLP 2018: 3497-3507 - [c89]David A. Hanauer, Qiaozhu Mei, V. G. Vinod Vydiswaran, Karandeep Singh, Zach Landis-Lewis, Chunhua Weng:
Numerical Age Variations within Clinical Notes: The Potential Impact on De-Identification and Information Extraction. ICHI Workshops 2018: 66-67 - [c88]Cheng Li, Xiaoxiao Guo, Qiaozhu Mei:
Joint Modeling of Text and Networks for Cascade Prediction. ICWSM 2018: 640-643 - [c87]Zhuofeng Wu, Cheng Li, Zhe Zhao, Fei Wu, Qiaozhu Mei:
Identify Shifts of Word Semantics through Bayesian Surprise. SIGIR 2018: 825-834 - [c86]Zhenpeng Chen, Xuan Lu, Wei Ai, Huoran Li, Qiaozhu Mei, Xuanzhe Liu:
Through a Gender Lens: Learning Usage Patterns of Emojis from Large-Scale Android Users. WWW 2018: 763-772 - [c85]Yunhao Jiao, Cheng Li, Fei Wu, Qiaozhu Mei:
Find the Conversation Killers: A Predictive Study of Thread-ending Posts. WWW 2018: 1145-1154 - [e1]Kevyn Collins-Thompson, Qiaozhu Mei, Brian D. Davison, Yiqun Liu, Emine Yilmaz:
The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR 2018, Ann Arbor, MI, USA, July 08-12, 2018. ACM 2018 [contents] - [i21]Huoran Li, Xuanzhe Liu, Qiaozhu Mei:
Predicting Smartphone Battery Life based on Comprehensive and Real-time Usage Data. CoRR abs/1801.04069 (2018) - [i20]Zhenpeng Chen, Sheng Shen, Ziniu Hu, Xuan Lu, Qiaozhu Mei, Xuanzhe Liu:
Ermes: Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification. CoRR abs/1806.02557 (2018) - [i19]Samuel Carton, Qiaozhu Mei, Paul Resnick:
Extractive Adversarial Networks: High-Recall Explanations for Identifying Personal Attacks in Social Media Posts. CoRR abs/1809.01499 (2018) - 2017
- [j17]Roy Chen, Yan Chen, Yang Liu, Qiaozhu Mei:
Does team competition increase pro-social lending? Evidence from online microfinance. Games Econ. Behav. 101: 311-333 (2017) - [j16]Xuan Lu, Zhenpeng Chen, Xuanzhe Liu, Huoran Li, Tao Xie, Qiaozhu Mei:
PRADO: Predicting App Adoption by Learning the Correlation between Developer-Controllable Properties and User Behaviors. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1(3): 79:1-79:30 (2017) - [j15]David A. Hanauer, Danny T. Y. Wu, Lei Yang, Qiaozhu Mei, Katherine B. Murkowski-Steffy, V. G. Vinod Vydiswaran, Kai Zheng:
Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine. J. Biomed. Informatics 67: 1-10 (2017) - [j14]Yukun Chen, Thomas A. Lasko, Qiaozhu Mei, Qingxia Chen, Sungrim Moon, Jingqi Wang, Ky Nguyen, Tolulola Dawodu, Trevor Cohen, Joshua C. Denny, Hua Xu:
An active learning-enabled annotation system for clinical named entity recognition. BMC Medical Informatics Decis. Mak. 17(2): 35-44 (2017) - [j13]Xuanzhe Liu, Wei Ai, Huoran Li, Jian Tang, Gang Huang, Feng Feng, Qiaozhu Mei:
Deriving User Preferences of Mobile Apps from Their Management Activities. ACM Trans. Inf. Syst. 35(4): 39:1-39:32 (2017) - [c84]Xinning Gui, Yue Wang, Yubo Kou, Tera L. Reynolds, Yunan Chen, Qiaozhu Mei, Kai Zheng:
Understanding the Patterns of Health Information Dissemination on Social Media during the Zika Outbreak. AMIA 2017 - [c83]Yue Wang, Kai Zheng, Hua Xu, Qiaozhu Mei:
Interactive Medical Word Sense Disambiguation with Instance and Feature Labeling. AMIA 2017 - [c82]Yue Wang, Jian Tang, V. G. Vinod Vydiswaran, Kai Zheng, Hua Xu, Qiaozhu Mei:
Matching Consumer Health Vocabulary with Professional Medical Terms Through Concept Embedding. AMIA 2017 - [c81]Alexander Kinsora, Kate Barron, Qiaozhu Mei, V. G. Vinod Vydiswaran:
Creating a Labeled Dataset for Medical Misinformation in Health Forums. ICHI 2017: 456-461 - [c80]Wei Ai, Xuan Lu, Xuanzhe Liu, Ning Wang, Gang Huang, Qiaozhu Mei:
Untangling Emoji Popularity Through Semantic Embeddings. ICWSM 2017: 2-11 - [c79]Jian Tang, Yue Wang, Kai Zheng, Qiaozhu Mei:
End-to-end Learning for Short Text Expansion. KDD 2017: 1105-1113 - [c78]Cheng Li, Xiaoxiao Guo, Qiaozhu Mei:
Deep Memory Networks for Attitude Identification. WSDM 2017: 671-680 - [c77]Cheng Li, Jiaqi Ma, Xiaoxiao Guo, Qiaozhu Mei:
DeepCas: An End-to-end Predictor of Information Cascades. WWW 2017: 577-586 - [i18]Cheng Li, Xiaoxiao Guo, Qiaozhu Mei:
Deep Memory Networks for Attitude Identification. CoRR abs/1701.04189 (2017) - [i17]Xuanzhe Liu, Huoran Li, Xuan Lu, Tao Xie, Qiaozhu Mei, Hong Mei, Feng Feng:
Understanding Diverse Smarpthone Usage Patterns from Large-Scale Appstore-Service Profiles. CoRR abs/1702.05060 (2017) - [i16]Zhenpeng Chen, Xuan Lu, Sheng Shen, Wei Ai, Xuanzhe Liu, Qiaozhu Mei:
Through a Gender Lens: An Empirical Study of Emoji Usage over Large-Scale Android Users. CoRR abs/1705.05546 (2017) - [i15]Ziniu Hu, Yun Ma, Qiaozhu Mei, Jian Tang:
Roaming across the Castle Tunnels: an Empirical Study of Inter-App Navigation Behaviors of Android Users. CoRR abs/1706.08274 (2017) - [i14]Jian Tang, Yue Wang, Kai Zheng, Qiaozhu Mei:
End-to-end Learning for Short Text Expansion. CoRR abs/1709.00389 (2017) - [i13]Yunhao Jiao, Cheng Li, Fei Wu, Qiaozhu Mei:
Find the Conversation Killers: a Predictive Study of Thread-ending Posts. CoRR abs/1712.08636 (2017) - 2016
- [j12]Danny T. Y. Wu, David A. Hanauer, Qiaozhu Mei, Patricia M. Clark, Lawrence C. An, Joshua Proulx, Qing T. Zeng, V. G. Vinod Vydiswaran, Kevyn Collins-Thompson, Kai Zheng:
Assessing the readability of ClinicalTrials.gov. J. Am. Medical Informatics Assoc. 23(2): 269-275 (2016) - [j11]Huaiyu Wan, Marie-Francine Moens, Walter Luyten, Xuezhong Zhou, Qiaozhu Mei, Lu Liu, Jie Tang:
Extracting relations from traditional Chinese medicine literature via heterogeneous entity networks. J. Am. Medical Informatics Assoc. 23(2): 356-365 (2016) - [c76]Yue Wang, Kai Zheng, Hua Xu, Qiaozhu Mei:
Clinical Word Sense Disambiguation with Interactive Search and Classification. AMIA 2016 - [c75]Cheng Li, Paul Resnick, Qiaozhu Mei:
Multiple Queries as Bandit Arms. CIKM 2016: 1089-1098 - [c74]Xuan Lu, Wei Ai, Xuanzhe Liu, Qian Li, Ning Wang, Gang Huang, Qiaozhu Mei:
Learning from the ubiquitous language: an empirical analysis of emoji usage of smartphone users. UbiComp 2016: 770-780 - [c73]Xuan Lu, Xuanzhe Liu, Huoran Li, Tao Xie, Qiaozhu Mei, Dan Hao, Gang Huang, Feng Feng:
PRADA: prioritizing android devices for apps by mining large-scale usage data. ICSE 2016: 3-13 - [c72]Xuan Lu, Xuanzhe Liu, Huoran Li, Tao Xie, Qiaozhu Mei, Dan Hao, Gang Huang, Feng Feng:
Mining usage data from large-scale Android users: challenges and opportunities. MOBILESoft 2016: 301-302 - [c71]Yue Wang, Dawei Yin, Luo Jie, Pengyuan Wang, Makoto Yamada, Yi Chang, Qiaozhu Mei:
Beyond Ranking: Optimizing Whole-Page Presentation. WSDM 2016: 103-112 - [c70]Xin Rong, Zhe Chen, Qiaozhu Mei, Eytan Adar:
EgoSet: Exploiting Word Ego-networks and User-generated Ontology for Multifaceted Set Expansion. WSDM 2016: 645-654 - [c69]Jian Tang, Jingzhou Liu, Ming Zhang, Qiaozhu Mei:
Visualizing Large-scale and High-dimensional Data. WWW 2016: 287-297 - [c68]Huoran Li, Wei Ai, Xuanzhe Liu, Jian Tang, Gang Huang, Feng Feng, Qiaozhu Mei:
Voting with Their Feet: Inferring User Preferences from App Management Activities. WWW 2016: 1351-1362 - [i12]V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, Rand Waltzman, Andrew Stevens, Alexander Dekhtyar, Shuyang Gao, Tad Hogg, Farshad Kooti, Yan Liu, Onur Varol, Prashant Shiralkar, V. G. Vinod Vydiswaran, Qiaozhu Mei, Tim Huang:
The DARPA Twitter Bot Challenge. CoRR abs/1601.05140 (2016) - [i11]Jian Tang, Jingzhou Liu, Ming Zhang, Qiaozhu Mei:
Visualization Large-scale and High-dimensional Data. CoRR abs/1602.00370 (2016) - [i10]Cheng Li, Xiaoxiao Guo, Qiaozhu Mei:
DeepGraph: Graph Structure Predicts Network Growth. CoRR abs/1610.06251 (2016) - [i9]Cheng Li, Jiaqi Ma, Xiaoxiao Guo, Qiaozhu Mei:
DeepCas: an End-to-end Predictor of Information Cascades. CoRR abs/1611.05373 (2016) - [i8]Jian Tang, Meng Qu, Qiaozhu Mei:
Identity-sensitive Word Embedding through Heterogeneous Networks. CoRR abs/1611.09878 (2016) - [i7]Jian Tang, Yifan Yang, Samuel Carton, Ming Zhang, Qiaozhu Mei:
Context-aware Natural Language Generation with Recurrent Neural Networks. CoRR abs/1611.09900 (2016) - [i6]Jian Tang, Ming Zhang, Qiaozhu Mei:
Less is More: Learning Prominent and Diverse Topics for Data Summarization. CoRR abs/1611.09921 (2016) - 2015
- [j10]David A. Hanauer, Qiaozhu Mei, James Law, Ritu Khanna, Kai Zheng:
Supporting information retrieval from electronic health records: A report of University of Michigan's nine-year experience in developing and using the Electronic Medical Record Search Engine (EMERSE). J. Biomed. Informatics 55: 290-300 (2015) - [j9]Yukun Chen, Thomas A. Lasko, Qiaozhu Mei, Joshua C. Denny, Hua Xu:
A study of active learning methods for named entity recognition in clinical text. J. Biomed. Informatics 58: 11-18 (2015) - [c67]Yukun Chen, Sungrim Moon, Thomas A. Lasko, Qiaozhu Mei, Jingqi Wang, Trevor Cohen, Qingxia Chen, Joshua C. Denny, Hua Xu:
Real Time Active Learning Study for Clinical Named Entity Recognition. AMIA 2015 - [c66]Yang Liu, Tricia O'Brien, Esha Sondhi, Qiaozhu Mei, David A. Hanauer, Kai Zheng:
Caveats of Using Social Media Data for Medical Research: A Report from a Study on Eye-Related Symptoms in Tweets. AMIA 2015 - [c65]Tera L. Reynolds, V. G. Vinod Vydiswaran, Yuting Wu, Qiaozhu Mei, David A. Hanauer, Kai Zheng:
Identifying Patterns Indicative of Copying/Pasting Behavior in Patient Generated Online Content. AMIA 2015 - [c64]Yun Ma, Xuanzhe Liu, Meihua Yu, Yunxin Liu, Qiaozhu Mei, Feng Feng:
Mash Droid: An Approach to Mobile-Oriented Dynamic Services Discovery and Composition by In-App Search. ICWS 2015: 725-730 - [c63]Samuel Carton, Souneil Park, Nicole Zeffer, Eytan Adar, Qiaozhu Mei, Paul Resnick:
Audience Analysis for Competing Memes in Social Media. ICWSM 2015: 41-50 - [c62]Huoran Li, Xuan Lu, Xuanzhe Liu, Tao Xie, Kaigui Bian, Felix Xiaozhu Lin, Qiaozhu Mei, Feng Feng:
Characterizing Smartphone Usage Patterns from Millions of Android Users. Internet Measurement Conference 2015: 459-472 - [c61]Jian Tang, Meng Qu, Qiaozhu Mei:
PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks. KDD 2015: 1165-1174 - [c60]Cheng Li, Yue Lu, Qiaozhu Mei, Dong Wang, Sandeep Pandey:
Click-through Prediction for Advertising in Twitter Timeline. KDD 2015: 1959-1968 - [c59]Fengmin Hu, Danny T. Y. Wu, Qiaozhu Mei, V. G. Vinod Vydiswaran:
Learning from Medical Summaries: The University of Michigan at TREC 2015 Clinical Decision Support Track. TREC 2015 - [c58]