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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2013.10
- 수록면
- 1,077 - 1,088 (12page)
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High-dimensional data analysis arises from almost all scientific areas, evolving with development of computing skills, and has encouraged penalized estimations that play important roles in statistical learning. For the past years, various penalized estimations have been developed, and the least absolute shrinkage and selection operator (LASSO)proposed by Tibshirani (1996) has shown outstanding ability, earning the first place on the development of penalized estimation. In this paper, we first introduce a number of recent advances in high-dimensional data analysis using the LASSO. The topics include various statistical problems such as variable selection and grouped or structured variable selection under sparse high-dimensional linear regression models. Several unsupervised learning methods including inverse covariance matrix estimation are presented. In ad-dition, we address further studies on new applications which may establish a guideline on how to use the LASSO for statistical challenges of high-dimensional data analysis.
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참고문헌 (61)
참고문헌 신청
1. [학술대회논문] - Akaike, H. / 1973 / Information theory and an extension of the maximum likelihood principle / Proceedings Second International Symposium on Information Theory : 267 ~ 281
2. [학술대회논문] - Alon, U. / 1999 / Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays / Proceedings of the National Academy of Sciences of the USA 96 : 6745 ~ 6750
3. [학술지(정기간행물)] - Banerjee, O. / 2008 / Model selection through sparse maximum likelihood estimation for multivariate gaussian or binary data / Journal of Machine Learning Research 9 : 485 ~ 516
4. [학술지(정기간행물)] - Bickel, P. J. / 2009 / Simultaneous analysis of lasso and dantzig selector / The Annals of Statistics 37 : 1705 ~ 1732
5. [학술지(정기간행물)] - Breiman, L. / 1996 / Heuristics of instability and stabilization in model selection / The Annals of Statistics 24 : 2350 ~ 2383
2. [학술대회논문] - Alon, U. / 1999 / Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays / Proceedings of the National Academy of Sciences of the USA 96 : 6745 ~ 6750
3. [학술지(정기간행물)] - Banerjee, O. / 2008 / Model selection through sparse maximum likelihood estimation for multivariate gaussian or binary data / Journal of Machine Learning Research 9 : 485 ~ 516
4. [학술지(정기간행물)] - Bickel, P. J. / 2009 / Simultaneous analysis of lasso and dantzig selector / The Annals of Statistics 37 : 1705 ~ 1732
5. [학술지(정기간행물)] - Breiman, L. / 1996 / Heuristics of instability and stabilization in model selection / The Annals of Statistics 24 : 2350 ~ 2383
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UCI(KEPA) : I410-ECN-0101-2018-041-001383988