Fetching the paper…
Reading the bibliography…
This paper studies simultaneous feature selection and extraction in supervised and unsupervised learning.
Adaptive estimation in two-way sparse reduced-rank regression
Ma, Z., Ma, Z., and Sun, T. (2014b) · 1922
Earlier work this paper cites.
Analysis of a complex of statistical variables into principal components
Hotelling, H. (1933) · 1933
Earlier work this paper cites.
Estimating linear restrictions on regression coefficients for multivariate normal distributions
Anderson, T. W. (1951) · 1951
Earlier work this paper cites.
The risk inflation criterion for multiple regression
Foster, D. P. and George, E. I. (1994) · 1975
Earlier work this paper cites.
Nets of Grassmann manifold and orthogonal groups
Szarek, S. J. (1982) · 1982
Earlier work this paper cites.
Moderate projection pursuit regression for multivariate response data
Aldrin, M. (1996) · 1996
Earlier work this paper cites.
Multivariate Reduced-Rank Regression: Theory and Applications
Reinsel, G. and Velu, R. (1998) · 1998
Earlier work this paper cites.
A fast algorithm for the minimum covariance determinant estimator
Rousseeuw, P. and Van Driessen, K. (1999) · 1999
Earlier work this paper cites.
Adaptive estimation of a quadratic functional by model selection
Laurent, B. and Massart, P. (2000) · 2000
Earlier work this paper cites.
Variable selection via nonconcave penalized likelihood and its oracle properties
Fan, J. and Li, R. (2001) · 2001
Earlier work this paper cites.
From few to many: Illumination cone models for face recognition under variable lighting and pose
Georghiades, A., Belhumeur, P., and Kriegman, D. (2001) · 2001
Earlier work this paper cites.
Acquiring linear subspaces for face recognition under variable lighting
Lee, K., Ho, J., and Kriegman, D. (2005) · 2005
Earlier work this paper cites.
Model selection and estimation in regression with grouped variables
Yuan, M. and Lin, Y. (2006) · 2006
Earlier work this paper cites.
Sparse principal component analysis
Zou, H., Hastie, T. J., and Tibshirani, R. J. (2006) · 2006
Earlier work this paper cites.
Extended Bayesian information criterion for model selection with large model space
Chen, J. and Chen, Z. (2008) · 2008
Earlier work this paper cites.
Sure independence screening for ultrahigh dimensional feature space (with discussion)
Fan, J. and Lv, J. (2008) · 2008
Cited alongside, same era.
Modern Multivariate Statistical Techniques: Regression, Classification and Manifold Learning
Izenman, A. (2008) · 2008
Cited alongside, same era.
Linear and Nonlinear Programming
Luenberger, D. and Ye, Y. (2008) · 2008
Cited alongside, same era.
Sparse principal component analysis via regularized low rank matrix approximation
Shen, H. and Huang, J. (2008) · 2008
Cited alongside, same era.
Simultaneous analysis of lasso and Dantzig selector
Bickel, P. J., Ritov, Y., and Tsybakov, A. B. (2009) · 2009
Cited alongside, same era.
The Elements of Statistical Learning
Hastie, T. J., Tibshirani, R. J., and Friedman, J. H. (2009) · 2009
Cited alongside, same era.
Estimation of high-dimensional low-rank matrices
Rohde, A. and Tsybakov, A. B. (2011) · 2011
Later among the works it cites.
Joint variable and ank selection for parsimonious estimation of high dimensional matrices
Bunea, F., She, Y., and Wegkamp, M. (2012) · 2012
Later among the works it cites.
Reduced rank stochastic regression with a sparse singular value decomposition
Chen, K., Chan, K.-S., and Stenseth, N. C. (2012) · 2012
Later among the works it cites.
Sparse reduced-rank regression for simultaneous dimension reduction and variable selection
Chen, L. and Huang, J. Z. (2012) · 2012
Later among the works it cites.
An iterative algorithm for fitting nonconvex penalized generalized linear models with grouped predictors
She, Y. (2012) · 2012
Later among the works it cites.
Generalized shrinkage methods for forecasting using many predictors
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
On consistency and sparsity for principal components analysis in high dimensions
Johnstone, I. M. and Lu, A. Y. (2009) · 2009
Cited alongside, same era.
On the conditions used to prove oracle results for the lasso
van de Geer, S. A. and Bühlmann, P. (2009) · 2009
Cited alongside, same era.
A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
Witten, D., Tibshirani, R. J., and Hastie, T. J. (2009) · 2009
Cited alongside, same era.
Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
Recht, B., Fazel, M., and Parrilo, P. A. (2010) · 2010
Cited alongside, same era.
Consistent group selection in high-dimensional linear regression
Wei, F. and Huang, J. (2010) · 2010
Cited alongside, same era.
Optimal selection of reduced rank estimators of high-dimensional matrices
Bunea, F., She, Y., and Wegkamp, M. (2011) · 2011
Cited alongside, same era.
Stock, J. H. and Watson, M. W. (2012) · 2012
Later among the works it cites.
A general theory of concave regularization for high dimensional sparse estimation problems
Zhang, C.-H. and Zhang, T. (2012) · 2012
Later among the works it cites.
Complexity theoretic lower bounds for sparse principal component detection
Berthet, A. and Rigollet, P. (2013) · 2013
Later among the works it cites.
Sparse PCA: Optimal rates and adaptive estimation
Cai, T. T., Ma, Z., and Wu, Y. (2013) · 2013
Later among the works it cites.
Sparse principal component analysis and iterative thresholding
Ma, Z. (2013) · 2013
Later among the works it cites.
Reduced rank vector generalized linear models for feature extraction
She, Y. (2013) · 2013
Later among the works it cites.
Upper and Lower Bounds for Stochastic Processes: Modern Methods and Classical Problems, volume 60
Talagrand, M. (2014) · 2014
Closest in time.
Sparse CCA: Adaptive estimation and computational barriers
Gao, C., Ma, Z., and Zhou, H. (2016) · 2016
Closest in time.
On the finite-sample analysis of
She, Y. (2016) · 2016
Closest in time.