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The Chinese Dialects of Han Time According to Fang Yen
1959
Journal of the American Oriental Society
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The Fang yen is probably the most important
source from which one may have some idea of the distribution of dialects in Han time. ...
JOHN ALEXANDER POPE FREER GALLERY OF ART
GLOSSARY
a A
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The Chinese Dialects of Han Time According to Fang Yen. By Pauw L-M. SERRvysS, C.1.C.M. ...
doi:10.2307/595155
fatcat:tfnnuxt4nffkpp3crval6ezgse
On the Study of Han-Fang-Chi (_??__??__??_)
漢防已ノ研究 第2報
1934
Nippon Yakubutsugaku Zasshi (Folia Pharmacologica Japonica)
漢防已ノ研究 第2報
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Rapid identification of apolipoprotein E genotypes by high-resolution melting analysis in Chinese Han and African Fang populations
2014
Experimental and Therapeutic Medicine
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A total of 100 healthy Southern Chinese Han and 175 healthy African Fang individuals attended the study. ...
For this reason, an HRM analysis was used in the present study for APOE genotyping in the Southern Chinese Han and African Fang populations. ...
Table Ⅱ . Ⅱ Frequencies of apolipoprotein E genotypes in the Southern Chinese Han and African Fang populations. ...
doi:10.3892/etm.2014.2097
pmid:25574218
pmcid:PMC4280925
fatcat:dz5tlkc3kzf4pe3s4qwjbuf4je
The Nonparanormal SKEPTIC
[article]
2012
arXiv
pre-print
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The research of Han Liu, John Lafferty, and Larry Wasserman was supported by NSF grant IIS-1116730 and AFOSR contract FA9550-09-1-0373. ...
arXiv:1206.6488v1
fatcat:d2ivmwocpfa7lbau6tnzhcatm4
High Dimensional Semiparametric Scale-Invariant Principal Component Analysis
[article]
2014
arXiv
pre-print
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We propose a new high dimensional semiparametric principal component analysis (PCA) method, named Copula Component Analysis (COCA). The semiparametric model assumes that, after unspecified marginally monotone transformations, the distributions are multivariate Gaussian. COCA improves upon PCA and sparse PCA in three aspects: (i) It is robust to modeling assumptions; (ii) It is robust to outliers and data contamination; (iii) It is scale-invariant and yields more interpretable results. We prove
arXiv:1402.4507v1
fatcat:rw6qu2gpnretlf6n2c3qwnowgi
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... hat the COCA estimators obtain fast estimation rates and are feature selection consistent when the dimension is nearly exponentially large relative to the sample size. Careful experiments confirm that COCA outperforms sparse PCA on both synthetic and real-world datasets.
Transelliptical Component Analysis
2012
Neural Information Processing Systems
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Elliptical distribution family includes many well-known multivariate distributions like multivariate Gaussian, t and logistic and it is extended to the meta-elliptical by Fang et.al (2002) using the copula ...
dblp:conf/nips/HanL12a
fatcat:3w2owrvzbjghxbg77rrrcwrova
Robust Inference of Risks of Large Portfolios
[article]
2015
arXiv
pre-print
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For example, Han and Liu (2014b) , Han and Liu (2013a) , Wegkamp and Zhao (2013) , Mitra and Zhang (2014) , and Fan et al. (2014) exploit the rank statistics, while Qiu et al. (2014) focus on quantile ...
2011 Fan et al., , 2013 Han and Liu, 2013b) , and physical dependence (Xiao and Wu, 2012; Chen et al., 2013) . ...
arXiv:1501.02382v1
fatcat:7o3hvbifgnfj3ovse4gdags4xy
Association of NCAM1 Polymorphisms with Autism and Parental Age at Conception in a Chinese Han Population
2014
Genetic Testing and Molecular Biomarkers
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The healthy control subjects consisted of 451 (408 males and 43 females, aged 18-48 years old) Chinese Han subjects. ...
According to our results, NCAM1 polymorphisms might be associated with autism, especially in the Chinese Han population. ...
doi:10.1089/gtmb.2014.0055
pmid:25137309
pmcid:PMC4183898
fatcat:6c6outdnyvd7hejqfwvb3isrru
Transelliptical Graphical Models
2012
Neural Information Processing Systems
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We advocate the use of a new distribution family-the transelliptical-for robust inference of high dimensional graphical models. The transelliptical family is an extension of the nonparanormal family proposed by Liu et al. (2009) . Just as the nonparanormal extends the normal by transforming the variables using univariate functions, the transelliptical extends the elliptical family in the same way. We propose a nonparametric rank-based regularization estimator which achieves the parametric rates
dblp:conf/nips/LiuHZ12
fatcat:fzvxrctlwzdibn55ymr5xjrkpa
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... of convergence for both graph recovery and parameter estimation. Such a result suggests that the extra robustness and flexibility obtained by the semiparametric transelliptical modeling incurs almost no efficiency loss. We also discuss the relationship between this work with the transelliptical component analysis proposed by .
Paternalistic Leadership and Employees' Sustained Work Behavior: A Perspective of Playfulness
2019
Sustainability
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The frontline employees of the service industry are the first connection between enterprises and consumers. Therefore, their performance often represents the image of the company. This study intended to discuss employees' sustained work behavior through the perceived organizational climate, from the point of view of direct supervisors' leadership. Employees of chain convenience stores in Taiwan were used as the research samples for the questionnaire survey. A total of 473 valid questionnaires
doi:10.3390/su11236650
fatcat:w2jis5fmdfafxmiv7falwl6lje
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... re considered using structural equation analyses. The results showed that authoritarian leadership and employees' turnover intentions had a significant positive relationship; moreover, there were negative relations between moral leadership, benevolent leadership, and employees' turnover intention. Thus, employees' perceived playfulness can decrease turnover intention when under paternalistic leadership. This study provides valuable insights for managers to understand the work value of playfulness.
Crystal structure of 2-(4-methylbenzoyl)pyrene, C24H16O
2016
Zeitschrift für Kristallographie - New Crystal Structures
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, Xuzhou 221116, Jiangsu Province, People's Republic of China, e-mail: zhanglifang@cumt.edu.cn Zhang *Corresponding
Ran and Han Fang-Fang: School of Chemical Engineering and Technology, China University ...
These chains are linked by π-π and C-H-π interactions, giving a three-dimensional network. author: Zhang Li-Fang, School of Chemical Engineering and Technology, China University of Mining and Technology ...
doi:10.1515/ncrs-2015-0292
fatcat:552uhhgmtjggva5ly4o7a27lcy
Robust Portfolio Optimization
2015
Neural Information Processing Systems
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We propose a robust portfolio optimization approach based on quantile statistics. The proposed method is robust to extreme events in asset returns, and accommodates large portfolios under limited historical data. Specifically, we show that the risk of the estimated portfolio converges to the oracle optimal risk with parametric rate under weakly dependent asset returns. The theory does not rely on higher order moment assumptions, thus allowing for heavy-tailed asset returns. Moreover, the rate
dblp:conf/nips/QiuHLC15
fatcat:4bu4hb5vzbfmtchtt3awtfvdby
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... convergence quantifies that the size of the portfolio under management is allowed to scale exponentially with the sample size of the historical data. The empirical effectiveness of the proposed method is demonstrated under both synthetic and real stock data. Our work extends existing ones by achieving robustness in high dimensions, and by allowing serial dependence.
Linking Neural Activity to Mental Processes
2008
Brain Imaging and Behavior
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Fang et al. (2007) localized face viewing representation combining the physical measurement and the adaptation of BOLD signals. ...
and Fang et al. (2007) also examined correlations between FFA activity and a perceptual illusion of face, namely, the viewpoint aftereffect. ...
doi:10.1007/s11682-008-9030-7
fatcat:aukt3e4hvrdyrngri6hc3jhmj4
Sparse Principal Component Analysis for High Dimensional Vector Autoregressive Models
[article]
2013
arXiv
pre-print
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We study sparse principal component analysis for high dimensional vector autoregressive time series under a doubly asymptotic framework, which allows the dimension d to scale with the series length T. We treat the transition matrix of time series as a nuisance parameter and directly apply sparse principal component analysis on multivariate time series as if the data are independent. We provide explicit non-asymptotic rates of convergence for leading eigenvector estimation and extend this result
arXiv:1307.0164v1
fatcat:wuhqobum5bemdfl5ln3xl7cf4y
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... to principal subspace estimation. Our analysis illustrates that the spectral norm of the transition matrix plays an essential role in determining the final rates. We also characterize sufficient conditions under which sparse principal component analysis attains the optimal parametric rate. Our theoretical results are backed up by thorough numerical studies.
Sparse Median Graphs Estimation in a High Dimensional Semiparametric Model
[article]
2013
arXiv
pre-print
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In this manuscript a unified framework for conducting inference on complex aggregated data in high dimensional settings is proposed. The data are assumed to be a collection of multiple non-Gaussian realizations with underlying undirected graphical structures. Utilizing the concept of median graphs in summarizing the commonality across these graphical structures, a novel semiparametric approach to modeling such complex aggregated data is provided along with robust estimation of the median graph,
arXiv:1310.3223v1
fatcat:vp73uauxv5f3lkms3vzan3rmoq
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... which is assumed to be sparse. The estimator is proved to be consistent in graph recovery and an upper bound on the rate of convergence is given. Experiments on both synthetic and real datasets are conducted to illustrate the empirical usefulness of the proposed models and methods.
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