-
1
-
-
84945116550
-
Sliced inverse regression for dimension reduction
-
K. C. Li, "Sliced inverse regression for dimension reduction," Journal of the American Statistical Association, vol. 86, no. 414, pp. 316-327, 1991.
-
(1991)
Journal of the American Statistical Association
, vol.86
, Issue.414
, pp. 316-327
-
-
Li, K.C.1
-
2
-
-
0038713181
-
Using linear smoothers to assess the structural dimension of regressions
-
E. Bura, "Using linear smoothers to assess the structural dimension of regressions," Statistica Sinica, vol. 13, 2003.
-
(2003)
Statistica Sinica
, vol.13
-
-
Bura, E.1
-
3
-
-
77957756004
-
Dimension estimation in sufficient dimension reduction: A unifying approach
-
E. Bura and J. Yang, "Dimension estimation in sufficient dimension reduction: A unifying approach," Journal of Multivariate Analysis, vol. 102, no. 1, pp. 130-142, 2011.
-
(2011)
Journal of Multivariate Analysis
, vol.102
, Issue.1
, pp. 130-142
-
-
Bura, E.1
Yang, J.2
-
6
-
-
0036428498
-
An adaptive estimation of dimension reduction subspace
-
Y. Xia, H. Tong, W. K. Li, and L. X. Zhu, "An adaptive estimation of dimension reduction subspace," Journal of the Royal Statistical Society: Series B, vol. 64, pp. 363-410, 2002.
-
(2002)
Journal of the Royal Statistical Society: Series B
, vol.64
, pp. 363-410
-
-
Xia, Y.1
Tong, H.2
Li, W.K.3
Zhu, L.X.4
-
7
-
-
0022150259
-
Fading memory and the problem of approximating nonlinear operators with Volterra series
-
S. Boyd and L. O. Chua, "Fading memory and the problem of approximating nonlinear operators with Volterra series," IEEE Trans. Circuits Syst., vol. 32, no. 11, 1985.
-
(1985)
IEEE Trans. Circuits Syst.
, vol.32
, Issue.11
-
-
Boyd, S.1
Chua, L.O.2
-
10
-
-
0032216898
-
The geometry of algorithms with orthogonality constraints
-
A. Edelman, A. Tomás, and T. Steven, "The geometry of algorithms with orthogonality constraints," SIAM Journal on Matrix Analysis and Applications, vol. 20, no. 2, pp. 303-353, 1998.
-
(1998)
SIAM Journal on Matrix Analysis and Applications
, vol.20
, Issue.2
, pp. 303-353
-
-
Edelman, A.1
Tomás, A.2
Steven, T.3
-
13
-
-
85162034614
-
Guaranteed rank minimization via singular value projection
-
P. Jain, R. Meka, and I. Dhillon, "Guaranteed rank minimization via singular value projection," in Proceedings of the 23rd Annual Conference on Advances in Neural Information Processing Systems, 2010, pp. 937-945.
-
(2010)
Proceedings of the 23rd Annual Conference on Advances in Neural Information Processing Systems
, pp. 937-945
-
-
Jain, P.1
Meka, R.2
Dhillon, I.3
-
15
-
-
0001287271
-
Regression shrinkage and selection via the Lasso
-
R. Tibshirani, "Regression shrinkage and selection via the Lasso," Journal of the Royal Statistical Society: Series B, vol. 58, no. 1, pp. 267-288, 1996.
-
(1996)
Journal of the Royal Statistical Society: Series B
, vol.58
, Issue.1
, pp. 267-288
-
-
Tibshirani, R.1
-
16
-
-
72549110327
-
Interior-point method for nuclear norm approximation with applications to system identification
-
Z. Liu and L. Vandenberghe, "Interior-point method for nuclear norm approximation with applications to system identification," SIAM Journal on Matrix Analysis and Applications, vol. 31, no. 3, pp. 1235-1256, 2009.
-
(2009)
SIAM Journal on Matrix Analysis and Applications
, vol.31
, Issue.3
, pp. 1235-1256
-
-
Liu, Z.1
Vandenberghe, L.2
-
18
-
-
84865420837
-
An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems
-
K. C. Toh and S. Yun, "An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems," Optimization online, 2009.
-
(2009)
Optimization Online
-
-
Toh, K.C.1
Yun, S.2
-
20
-
-
0030197651
-
Identifying MIMO Wiener systems using subspace model identification methods
-
D. Westwick and M. Verhaegen, "Identifying MIMO Wiener systems using subspace model identification methods," Signal Processing, vol. 52, no. 2, 1996.
-
(1996)
Signal Processing
, vol.52
, Issue.2
-
-
Westwick, D.1
Verhaegen, M.2
-
21
-
-
0002334592
-
A new identification and model reduction algorithm via singular value decomposition
-
Pacific Grove, CA, USA
-
S. Y. Kung, "A new identification and model reduction algorithm via singular value decomposition," in Proceedings of the 12th Asilomar Conference on Circuits, Systems and Computers, Pacific Grove, CA, USA, 1978, pp. 705-714.
-
(1978)
Proceedings of the 12th Asilomar Conference on Circuits, Systems and Computers
, pp. 705-714
-
-
Kung, S.Y.1
-
22
-
-
20444454672
-
Sufficient dimension reduction via inverse regression: A minimum discrepancy approach
-
R. D. Cook and L. Ni, "Sufficient dimension reduction via inverse regression: A minimum discrepancy approach," Journal of the American Statistical Association, vol. 100, no. 470, pp. 410-428, 2011.
-
(2011)
Journal of the American Statistical Association
, vol.100
, Issue.470
, pp. 410-428
-
-
Cook, R.D.1
Ni, L.2
-
23
-
-
68649110509
-
Dimension reduction for nonelliptically distributed predictors
-
B. Li and Y. Dong, "Dimension reduction for nonelliptically distributed predictors," The Annals of Statistics, vol. 37, no. 3, pp. 1272-1298, 2009.
-
(2009)
The Annals of Statistics
, vol.37
, Issue.3
, pp. 1272-1298
-
-
Li, B.1
Dong, Y.2
-
24
-
-
77952861561
-
Dimension reduction for non-elliptically distributed regressors: Second-order methods
-
Y. Dong and B. Li, "Dimension reduction for non-elliptically distributed regressors: Second-order methods," Biometrica, vol. 97, no. 2, pp. 279-294, 2010.
-
(2010)
Biometrica
, vol.97
, Issue.2
, pp. 279-294
-
-
Dong, Y.1
Li, B.2
|