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正則化 (Japanese Wikipedia)

Analysis of information sources in references of the Wikipedia article "正則化" in Japanese language version.

refsWebsite
Global rank Japanese rank
4doi.org
2nd place
6th place
2ams.org
451st place
1,252nd place
2arxiv.org
69th place
227th place
2stanford.edu
179th place
608th place
1worldcat.org
5th place
19th place
1jstor.org
26th place
275th place
1aclweb.org
low place
low place

aclweb.org

ams.org

mathscinet.ams.org

  • Tibshirani, Robert (1996). “Regression Shrinkage and Selection via the Lasso”. Journal of the Royal Statistical Society, Series B 58 (1): 267–288. doi:10.1111/j.2517-6161.1996.tb02080.x. ISSN 1369-7412. JSTOR 2346178. MR1379242. http://statweb.stanford.edu/~tibs/lasso/lasso.pdf. 
  • Candes, Emmanuel; Tao, Terence (2007). “The Dantzig selector: Statistical estimation when p is much larger than n”. Annals of Statistics 35 (6): 2313–2351. arXiv:math/0506081. doi:10.1214/009053606000001523. MR2382644. 

arxiv.org

  • Candes, Emmanuel; Tao, Terence (2007). “The Dantzig selector: Statistical estimation when p is much larger than n”. Annals of Statistics 35 (6): 2313–2351. arXiv:math/0506081. doi:10.1214/009053606000001523. MR2382644. 
  • Małgorzata Bogdan, Ewout van den Berg, Weijie Su & Emmanuel J. Candes (2013). “Statistical estimation and testing via the ordered L1 norm”. arXiv preprint arXiv:1310.1969. arXiv:1310.1969v2. 

doi.org

  • Tibshirani, Robert (1996). “Regression Shrinkage and Selection via the Lasso”. Journal of the Royal Statistical Society, Series B 58 (1): 267–288. doi:10.1111/j.2517-6161.1996.tb02080.x. ISSN 1369-7412. JSTOR 2346178. MR1379242. http://statweb.stanford.edu/~tibs/lasso/lasso.pdf. 
  • Galen Andrew; Jianfeng Gao (2007). “Scalable training of L₁-regularized log-linear models”. Proceedings of the 24th International Conference on Machine Learning. doi:10.1145/1273496.1273501. ISBN 9781595937933. 
  • Li Wang, Michael D. Gordon & Ji Zhu (2006). "Regularized Least Absolute Deviations Regression and an Efficient Algorithm for Parameter Tuning". Sixth International Conference on Data Mining. pp. 690–700. doi:10.1109/ICDM.2006.134。
  • Candes, Emmanuel; Tao, Terence (2007). “The Dantzig selector: Statistical estimation when p is much larger than n”. Annals of Statistics 35 (6): 2313–2351. arXiv:math/0506081. doi:10.1214/009053606000001523. MR2382644. 

jstor.org

  • Tibshirani, Robert (1996). “Regression Shrinkage and Selection via the Lasso”. Journal of the Royal Statistical Society, Series B 58 (1): 267–288. doi:10.1111/j.2517-6161.1996.tb02080.x. ISSN 1369-7412. JSTOR 2346178. MR1379242. http://statweb.stanford.edu/~tibs/lasso/lasso.pdf. 

stanford.edu

statweb.stanford.edu

  • Tibshirani, Robert (1996). “Regression Shrinkage and Selection via the Lasso”. Journal of the Royal Statistical Society, Series B 58 (1): 267–288. doi:10.1111/j.2517-6161.1996.tb02080.x. ISSN 1369-7412. JSTOR 2346178. MR1379242. http://statweb.stanford.edu/~tibs/lasso/lasso.pdf. 

web.stanford.edu

worldcat.org

search.worldcat.org

  • Tibshirani, Robert (1996). “Regression Shrinkage and Selection via the Lasso”. Journal of the Royal Statistical Society, Series B 58 (1): 267–288. doi:10.1111/j.2517-6161.1996.tb02080.x. ISSN 1369-7412. JSTOR 2346178. MR1379242. http://statweb.stanford.edu/~tibs/lasso/lasso.pdf.