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Aberrant Dynamic Functional Network Connectivity and Graph Properties in Major Depressive Disorder 期刊论文
FRONTIERS IN PSYCHIATRY, 2018, 卷号: 9, 期号: 1, 页码: 11
作者:  Zhi, Dongmei;  Calhoun, Vince D.;  Lv, Luxian;  Ma, Xiaohong;  Ke, Qing;  Fu, Zening;  Du, Yuhui;  Yang, Yongfeng;  Yang, Xiao;  Pan, Miao;  Qi, Shile;  Jiang, Rongtao;  Yu, Qingbao;  Sui, Jing
Adobe PDF(2635Kb)  |  收藏  |  浏览/下载：338/16  |  提交时间：2018/10/10
Major Depressive Disorder  Independent Component Analysis  Dynamic Functional Network Connectivity  Graph Theory  Resting-state Functional Magnetic Resonance Imaging  
Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia. 期刊论文
IEEE Trans Med Imaging., 2018, 卷号: 37(1), 期号: 201801, 页码: 93-105
作者:  Shile Qi;  Vince D. Calhoun;  Theo G. M. van Erp;  Juan Bustillo;  Eswar Damaraju;  Jessica A. Turner;  Yuhui Du;  Jiayu Chen;  Qingbao Yu;  Daniel H. Mathalon;  Judith M. Ford;  James Voyvodic;  Bryon A. Mueller;  Aysenil Belger;  Sarah Mc Ewen;  Steven G. Potkin;  Steven G. Potkin;  Tianzi Jiang;  Sui Jing(隋婧)
浏览  |  Adobe PDF(1484Kb)  |  收藏  |  浏览/下载：500/136  |  提交时间：2018/01/08
Multimodal Fusion With Reference  Mccar  Supervised Learning  Schizophrenia  Working Memory  Ica  Mccb  Cminds  
Inter and intra-hemispheric structural imaging markers predict depression relapse after electroconvulsive therapy: a multisite study 期刊论文
TRANSLATIONAL PSYCHIATRY, 2017, 卷号: 7, 期号: 12, 页码: 1270
作者:  Wade, Benjamin S. C.;  Sui, Jing;  Hellemann, Gerhard;  Leaver, Amber M.;  Espinoza, Randall T.;  Woods, Roger P.;  Abbott, Christopher C.;  Joshi, Shantanu H.;  Narr, Katherine L.
Adobe PDF(783Kb)  |  收藏  |  浏览/下载：405/75  |  提交时间：2018/01/08
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Building Energy Consumption Prediction: An Extreme Deep Learning Approach 期刊论文
ENERGIES, 2017, 卷号: 10, 期号: 10, 页码: 1-20
作者:  Li, Chengdong;  Ding, Zixiang;  Zhao, Dongbin;  Yi, Jianqiang;  Zhang, Guiqing
Adobe PDF(1918Kb)  |  收藏  |  浏览/下载：313/49  |  提交时间：2017/12/30
Building Energy Consumption  Deep Learning  Stacked Autoencoders  Extreme Learning Machine  
Parameter Identifiability in Statistical Machine Learning: A Review 期刊论文
NEURAL COMPUTATION, 2017, 卷号: 29, 期号: 5, 页码: 1151-1203
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
浏览  |  Adobe PDF(466Kb)  |  收藏  |  浏览/下载：326/97  |  提交时间：2017/07/18
Parameter Identifiability  Statistical Machine Learning  
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls 期刊论文
NEUROIMAGE, 2017, 卷号: 145, 页码: 137-165
作者:  Arbabshirani, Mohammad R.;  Plis, Sergey;  Sui, Jing;  Calhoun, Vince D.
Adobe PDF(2676Kb)  |  收藏  |  浏览/下载：457/114  |  提交时间：2017/02/14
Neuroimaging  Machine Learning  Classification  Brain Disorders  Prediction  
Multi-modal multiple kernel learning for accurate identification of Tourette syndrome children 期刊论文
PATTERN RECOGNITION, 2017, 卷号: 63, 期号: *, 页码: 601-611
作者:  Wen, Hongwei;  Liu, Yue;  Rekik, Islem;  Wang Shengpei;  Chen, Zhiqiang;  Zhang, Jishui;  Zhang, Yue;  Peng, Yun;  He, Huiguang
浏览  |  Adobe PDF(1101Kb)  |  收藏  |  浏览/下载：623/182  |  提交时间：2017/02/14
Tourette Syndrome  Dti  Tbss  Svm  Mkl  
Multimedia News Summarization in Search 期刊论文
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2016, 卷号: 7, 期号: 3
作者:  Li, Zechao;  Tang, Jinhui;  Wang, Xueming;  Liu, Jing;  Lu, Hanqing
Adobe PDF(1304Kb)  |  收藏  |  浏览/下载：472/196  |  提交时间：2016/10/20
Design  Algorithms  Performance  Human Factors  News Summarization  Topic Structure  Multimodal  Hierarchical Latent Dirichlet Allocation  Maximum Spanning Tree  
Social balance in signed networks 期刊论文
INFORMATION SYSTEMS FRONTIERS, 2015, 卷号: 17, 期号: 5, 页码: 1077-1095
作者:  Zheng, Xiaolong;  Zeng, Daniel;  Wang, Fei-Yue
浏览  |  Adobe PDF(761Kb)  |  收藏  |  浏览/下载：414/121  |  提交时间：2015/11/04
Social Balance  Signed Networks  Empirical Study  Dynamicsmodel  
Measuring the Visual Complexities of Web Pages 期刊论文
ACM TRANSACTIONS ON THE WEB, 2013, 卷号: 7, 期号: 1, 页码: 33
作者:  Wu, Ou;  Hu, Weiming;  Shi, Lei;  Ou Wu
浏览  |  Adobe PDF(1054Kb)  |  收藏  |  浏览/下载：414/135  |  提交时间：2015/08/12
Algorithms  Performance  Visual Complexity (Viscom)  Quantification  Web Mining  Feature  Learning