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北京大学 [4]

数学与系统科学研究院 [4]

地理科学与资源研究所 [2]

重庆绿色智能技术研究... [2]

青藏高原研究所 [1]

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	Ensemble-based deep learning for estimating PM2.5 over California with multisource big data including wildfire smoke 期刊论文 ENVIRONMENT INTERNATIONAL, 2020, 卷号: 145, 页码: 16 作者: Li, Lianfa; Girguis, Mariam; Lurmann, Frederick; Pavlovic, Nathan; McClure, Crystal 收藏 \| 浏览/下载：122/0 \| 提交时间：2021/03/16 PM2.5 Machine learning Air pollution exposure Wildfires Remote sensing California High spatiotemporal resolution
	Temporal Pattern-Aware QoS Prediction via Biased Non-Negative Latent Factorization of Tensors 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1798-1809 作者: Luo, Xin; Wu, Hao; Yuan, Huaqiang; Zhou, MengChu 收藏 \| 浏览/下载：16/0 \| 提交时间：2020/08/24 Quality of service Hidden Markov models Data models Training Web services Time factors Latent factor analysis (LFA) latent factorization of tensor learning temporal pattern linear bias (LB) non-negative latent factorization of tensor non-negativity constraint quality-of-service (QoS) prediction
	SUFFICIENT DIMENSION REDUCTION UNDER DIMENSION-REDUCTION-BASED IMPUTATION WITH PREDICTORS MISSING AT RANDOM 期刊论文 STATISTICA SINICA, 2019, 卷号: 29, 期号: 4, 页码: 1751-1778 作者: Yang, Xiaojie; Wang, Qihua 收藏 \| 浏览/下载：63/0 \| 提交时间：2020/01/10 Kernel imputation missing at random missing predictors sliced inverse regression sufficient dimension reduction
	Estimation of PM2.5 concentrations at a high spatiotemporal resolution using constrained mixed-effect bagging models with MAIAC aerosol optical depth 期刊论文 REMOTE SENSING OF ENVIRONMENT, 2018, 卷号: 217, 页码: 573-586 作者: Li, Lianfa; Zhang, Jiehao; Meng, Xia; Fang, Ying; Ge, Yong 收藏 \| 浏览/下载：33/0 \| 提交时间：2019/05/23 PM2.5 MAIAC AOD High spatiotemporal resolution Temporal variation AOD-PM2.5 associations Spatial effects Missingness Machine learning
	Reconstruction of MODIS Land Surface Temperature Products Based on Multi-Temporal Information 期刊论文 REMOTE SENSING, 2018, 卷号: 10, 期号: 7, 页码: 文献号 1112 作者: Zhang, Y (Zhang, Yang); Kang, J (Kang, Jian); Tan, JL (Tan, Junlei); Jin, R (Jin, Rui); Li, X (Li, Xin) 收藏 \| 浏览/下载：21/0 \| 提交时间：2019/05/29 AMSR2 OBSERVATIONS EMISSIVITY LST RADIATION VALIDATION REGRESSION
	How to Make Model-free Feature Screening Approaches for Full Data Applicable to the Case of Missing Response? 期刊论文 SCANDINAVIAN JOURNAL OF STATISTICS, 2018, 卷号: 45, 期号: 2, 页码: 324-346 作者: Wang, Qihua; Li, Yongjin 收藏 \| 浏览/下载：14/0 \| 提交时间：2018/07/30 borrowing missingness information missing data ultrahigh dimensionality variable screening
	Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2018, 卷号: 48, 期号: 4, 页码: 1216-1228 作者: Luo, Xin; Zhou, MengChu; Li, Shuai; Xia, Yunni; You, Zhu-Hong 收藏 \| 浏览/下载：26/0 \| 提交时间：2018/06/04 Big data latent factor model missing data prediction quality-of-service (QoS) second-order solver service computing sparse matrices Web service
	Dimension reduction based linear surrogate variable approach for model free variable selection 期刊论文 JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2016, 卷号: 169, 页码: 13-26 作者: Dai, Pengjie; Ding, Xiaobo; Wang, Qihua 收藏 \| 浏览/下载：19/0 \| 提交时间：2018/07/30 Adaptive LASSO Central subspace Linear surrogate variable Sufficient dimension reduction Variable selection
	Adaptive Logistic Group Lasso Method for Predicting the No-reflow among the Multiple Types of High-dimensional Variables with Missing Data 其他 2016-01-01 Yang, Xianglin; Tong, Yunhai; Meng, Xiangfeng; Zhao, Shuai; Xu, Zhi; Li, Yanjun; Jia, Xin; Tan, Shaohua 收藏 \| 浏览/下载：7/0 \| 提交时间：2017/12/03 no-reflow EMR adaptive group Lasso k-nearest neighbors (KNN) logistic regression prediction PERCUTANEOUS CORONARY INTERVENTION ELEVATION MYOCARDIAL-INFARCTION STATIN THERAPY REGRESSION SELECTION
	Adaptive Logistic Group Lasso Method for Predicting the No-reflow among the Multiple Types of High-dimensional Variables with Missing Data 其他 2016-01-01 Xianglin Yang; Yunhai Tong; Xiangfeng Meng; Shuai Zhao; Zhi Xu; Yanjun Li; Xin Jia; Shaohua Tan 收藏 \| 浏览/下载：5/0 \| 提交时间：2017/12/03 no-reflow EMR adaptive group Lasso k-nearest neighbors(KNN) logistic regression prediction no-reflow EMR adaptive group Lasso k-nearest neighbors(KNN) logistic regression prediction

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