Bayesian factor-adjusted sparse regression

Journal of Econometrics ◽

10.1016/j.jeconom.2020.06.012 ◽

2021 ◽

Author(s):

Jianqing Fan ◽

Bai Jiang ◽

Qiang Sun

Keyword(s):

Sparse Regression ◽

Bayesian Factor

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Sparse Regression Codes

10.1561/9781680835816 ◽

2019 ◽

Author(s):

Ranmji Venkataramanan ◽

Sekhar Tatikonda ◽

Andrew Barron

Keyword(s):

Sparse Regression

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Sparse regression for large data sets with outliers

European Journal of Operational Research ◽

10.1016/j.ejor.2021.05.049 ◽

2021 ◽

Author(s):

Lea Bottmer ◽

Christophe Croux ◽

Ines Wilms

Keyword(s):

Large Data Sets ◽

Data Sets ◽

Sparse Regression

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Projection neural network for a class of sparse regression problems with cardinality penalty

Neurocomputing ◽

10.1016/j.neucom.2020.12.045 ◽

2021 ◽

Vol 431 ◽

pp. 188-200

Author(s):

Wenjing Li ◽

Wei Bian

Keyword(s):

Neural Network ◽

Sparse Regression ◽

Regression Problems ◽

Projection Neural Network

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Safe Screening for Sparse Regression with the Kullback-Leibler Divergence

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp39728.2021.9414183 ◽

2021 ◽

Author(s):

Cassio F. Dantas ◽

Emmanuel Soubies ◽

Cedric Fevotte

Keyword(s):

Sparse Regression ◽

Leibler Divergence

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The structure of Chinese beginning online instructors’ competencies: evidence from Bayesian factor analysis

Journal of Computers in Education ◽

10.1007/s40692-021-00186-9 ◽

2021 ◽

Author(s):

Yang Wang ◽

Yixi Wang ◽

David Stein ◽

Qingtang Liu ◽

Wenli Chen

Keyword(s):

Factor Analysis ◽

Online Instructors ◽

Bayesian Factor ◽

Bayesian Factor Analysis

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Correction to: The structure of Chinese beginning online instructors’ competencies: evidence from Bayesian factor analysis

Journal of Computers in Education ◽

10.1007/s40692-021-00189-6 ◽

2021 ◽

Author(s):

Yixi Wang ◽

Yang Wang ◽

David Stein ◽

Qingtang Liu ◽

Wenli Chen

Keyword(s):

Factor Analysis ◽

Online Instructors ◽

Bayesian Factor ◽

Bayesian Factor Analysis

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Reducing Sampling Ratios and Increasing Number of Estimates Improve Bagging in Sparse Regression

2019 53rd Annual Conference on Information Sciences and Systems (CISS) ◽

10.1109/ciss.2019.8692865 ◽

2019 ◽

Author(s):

Luoluo Liu ◽

Sang Peter Chin ◽

Trac D. Tran

Keyword(s):

Sparse Regression

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Sparse Regression Based Structure Learning of Stochastic Reaction Networks from Single Cell Snapshot Time Series

PLoS Computational Biology ◽

10.1371/journal.pcbi.1005234 ◽

2016 ◽

Vol 12 (12) ◽

pp. e1005234 ◽

Author(s):

Anna Klimovskaia ◽

Stefan Ganscha ◽

Manfred Claassen

Keyword(s):

Time Series ◽

Single Cell ◽

Structure Learning ◽

Reaction Networks ◽

Sparse Regression ◽

Stochastic Reaction ◽

Stochastic Reaction Networks

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Fast Bayesian Factor Analysis via Automatic Rotations to Sparsity

Journal of the American Statistical Association ◽

10.1080/01621459.2015.1100620 ◽

2016 ◽

Vol 111 (516) ◽

pp. 1608-1622 ◽

Author(s):

Veronika Ročková ◽

Edward I. George

Keyword(s):

Factor Analysis ◽

Bayesian Factor ◽

Bayesian Factor Analysis

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Accounting for non-genetic factors by low-rank representation and sparse regression for eQTL mapping

Bioinformatics ◽

10.1093/bioinformatics/btt075 ◽

2013 ◽

Vol 29 (8) ◽

pp. 1026-1034 ◽

Author(s):

Can Yang ◽

Lin Wang ◽

Shuqin Zhang ◽

Hongyu Zhao

Keyword(s):

Genetic Factors ◽

Low Rank ◽

Eqtl Mapping ◽

Sparse Regression ◽

Low Rank Representation

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