Jiayu Zhou

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Jieping Ye, IEEE Fellow & ACM Distin...University of Michigan & BeikeVerified email at umich.edu
Fei WangAssociate Professor at Cornell UniversityVerified email at med.cornell.edu
Kaixiang LinApplied scientist, Amazon Web ServicesVerified email at msu.edu
Pang-Ning TanProfessor of Computer Science, Michigan State UniversityVerified email at cse.msu.edu
İnci M. BaytaşAssistant Professor at Bogazici UniversityVerified email at boun.edu.tr
Anil K. JainMichigan State UniversityVerified email at cse.msu.edu
Paul ThompsonProfessor of Neurology & Psychiatry, Imaging Genetics Center, USCVerified email at usc.edu
Liang ZhanDeps. of ECE and BioE, University of PittsburghVerified email at pitt.edu
Hiroko H. DodgeProfessor of Neurology, Oregon Health & Science University and University of MichiganVerified email at ohsu.edu
Shiyu ChangUniversity of California, Santa BarbaraVerified email at cs.ucsb.edu
Zhangyang (Atlas) WangUniversity of Texas at Austin & Amazon ResearchVerified email at utexas.edu
Yalin WangAssociate Professor of Computer Science and Engineering, Arizona State UniversityVerified email at asu.edu
Jianying HuIBM Thomas J. Wastson Research CenterVerified email at us.ibm.com
Lei YuanEngineering Manager, Machine Learning at FacebookVerified email at asu.edu
Thomas S. HuangUniversity of Illinois, Urbana-ChampaignVerified email at ifp.uiuc.edu
Shu WangPhD Candidate of Computer Science, Rutgers UniversityVerified email at cs.rutgers.edu
Guo-Jun Qi (齐国君), IEEE FellowComputer Science, University of Central FloridaVerified email at ucf.edu
Charu AggarwalDistinguished Research Staff Member, IBM T. J. Watson Research CenterVerified email at us.ibm.com
George KarypisDistinguished McKnight University Professor, CS&E, University of MinnesotaVerified email at umn.edu

Jiayu Zhou

Associate Professor at Michigan State University

Verified email at cse.msu.edu - Homepage

Machine Learning Data Mining Biomedical Informatics


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Patient subtyping via time-aware LSTM networks IM Baytas, C Xiao, X Zhang, F Wang, AK Jain, J Zhou Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017	396	2017
Malsar: Multi-task learning via structural regularization J Zhou, J Chen, J Ye Arizona State University 21, 1-50, 2011	352	2011
Clustered multi-task learning via alternating structure optimization J Zhou, J Chen, J Ye Advances in neural information processing systems 24, 2011	261	2011
Efficient large-scale fleet management via multi-agent deep reinforcement learning K Lin, R Zhao, Z Xu, J Zhou Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	249	2018
Differentially private generative adversarial network L Xie, K Lin, S Wang, F Wang, J Zhou arXiv preprint arXiv:1802.06739, 2018	242	2018
A multi-task learning formulation for predicting disease progression J Zhou, L Yuan, J Liu, J Ye Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011	234	2011
Integrating low-rank and group-sparse structures for robust multi-task learning J Chen, J Zhou, J Ye Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011	222	2011
Lasso Screening Rules via Dual Polytope Projection J Wang, J Zhou, P Wonka, J Ye NIPS, 2013	188	2013
Modeling disease progression via fused sparse group lasso J Zhou, J Liu, VA Narayan, J Ye Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012	188	2012
Modeling disease progression via multi-task learning J Zhou, J Liu, VA Narayan, J Ye, ... NeuroImage 78, 233-248, 2013	182	2013
Analysis of sampling techniques for imbalanced data: An n= 648 ADNI study R Dubey, J Zhou, Y Wang, PM Thompson, J Ye, ... NeuroImage 87, 220-241, 2014	170	2014
Graph convolutional networks for computational drug development and discovery M Sun, S Zhao, C Gilvary, O Elemento, J Zhou, F Wang Briefings in bioinformatics 21 (3), 919-935, 2020	145	2020
From micro to macro: data driven phenotyping by densification of longitudinal electronic medical records J Zhou, F Wang, J Hu, J Ye Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	137	2014
Who, what, when, and where: Multi-dimensional collaborative recommendations using tensor factorization on sparse user-generated data P Bhargava, T Phan, J Zhou, J Lee Proceedings of the 24th international conference on world wide web, 130-140, 2015	124	2015
An rnn architecture with dynamic temporal matching for personalized predictions of parkinson's disease C Che, C Xiao, J Liang, B Jin, J Zho, F Wang Proceedings of the 2017 SIAM international conference on data mining, 198-206, 2017	116	2017
Drug similarity integration through attentive multi-view graph auto-encoders T Ma, C Xiao, J Zhou, F Wang arXiv preprint arXiv:1804.10850, 2018	112	2018
Comparison of nine tractography algorithms for detecting abnormal structural brain networks in Alzheimer’s disease L Zhan, J Zhou, Y Wang, Y Jin, N Jahanshad, G Prasad, TM Nir, ... Frontiers in aging neuroscience 7, 48, 2015	107	2015
Missing modalities imputation via cascaded residual autoencoder L Tran, X Liu, J Zhou, R Jin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	96	2017
Transfer learning in deep reinforcement learning: A survey Z Zhu, K Lin, J Zhou arXiv preprint arXiv:2009.07888, 2020	86	2020
Learning a task-specific deep architecture for clustering Z Wang, S Chang, J Zhou, M Wang, TS Huang Proceedings of the 2016 SIAM International Conference on Data Mining, 369-377, 2016	77	2016

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