-
1
-
-
0000501656
-
Information theory and an extension of the maximum likelihood principle
-
(V. Petrov and F. Csáki, eds.) . Akadmiai Kiadó, Budapest
-
AKAIKE, H. (1973). Information theory and an extension of the maximum likelihood principle. In Proc. 2nd International Symposium on Information Theory (V. Petrov and F. Csáki, eds.) 267-281. Akadmiai Kiadó, Budapest.
-
(1973)
Proc. 2nd International Symposium on Information Theory
, pp. 267-281
-
-
Akaike, H.1
-
2
-
-
0442312210
-
Regularized wavelet approximations (with discussion)
-
ANTONIADIS, A. and FAN, J. (2001). Regularized wavelet approximations (with discussion). J. Amer. Statist. Assoc. 96 939-967.
-
(2001)
J. Amer. Statist. Assoc.
, vol.96
, pp. 939-967
-
-
Antoniadis, A.1
Fan, J.2
-
4
-
-
50849114939
-
Sparsity oracle inequalities for the lasso
-
electronic
-
BUNEA, F., TSYBAKOV, A. and WEGKAMP, M. (2007). Sparsity oracle inequalities for the lasso. Electron. J. Stat. 1 169-194 (electronic).
-
(2007)
Electron. J. Stat.
, vol.1
, pp. 169-194
-
-
Bunea, F.1
Tsybakov, A.2
Wegkamp, M.3
-
5
-
-
29144439194
-
Decoding by linear programming
-
CANDÉS, E. and TAO, T. (2005). Decoding by linear programming. IEEE Trans. Inform. Theory 51 4203-4215.
-
(2005)
IEEE Trans. Inform. Theory
, vol.51
, pp. 4203-4215
-
-
Candés, E.1
Tao, T.2
-
6
-
-
34548275795
-
The dantzig selector: Statistical estimation when p is much larger than n (with discussion)
-
CANDÉS, E. and TAO, T. (2007). The Dantzig selector: Statistical estimation when p is much larger than n (with discussion). Ann. Statist. 35 2313-2404.
-
(2007)
Ann. Statist.
, vol.35
, pp. 2313-2404
-
-
Candés, E.1
Tao, T.2
-
7
-
-
0003958737
-
On basis pursuit
-
Dept. Statistics, Stanford Univ.
-
CHEN, S. and DONOHO, D.L. (1994). On basis pursuit. Technical report, Dept. Statistics, Stanford Univ.
-
(1994)
Technical Report
-
-
Chen, S.1
Donoho, D.L.2
-
8
-
-
0012070851
-
Local operator theory, random matrices and Banach spaces
-
(W. B. Johnson and J. Lindenstrauss, eds.), North-Holland, Amsterdam
-
DAVIDSON, K. and SZAREK, S. (2001). Local operator theory, random matrices and Banach spaces. In Handbook on the Geometry of Banach Spaces (W. B. Johnson and J. Lindenstrauss, eds.) I 317-366. North-Holland, Amsterdam.
-
(2001)
Handbook on the Geometry of Banach Spaces
, vol.1
, pp. 317-366
-
-
Davidson, K.1
Szarek, S.2
-
10
-
-
0041958932
-
Ideal spatial adaptation by wavelet shrinkage
-
DONOHO, D. L. and JOHNSTONE, I. M. (1994b). Ideal spatial adaptation by wavelet shrinkage. Biometrika 81 425-455.
-
(1994)
Biometrika
, vol.81
, pp. 425-455
-
-
Donoho, D.L.1
Johnstone, I.M.2
-
11
-
-
0002712203
-
Maximum entropy and the nearly black object (with discussion)
-
DONOHO, D. L., JOHNSTONE, I. M., HOCH, J. C. and STERN, A. S. (1992). Maximum entropy and the nearly black object (with discussion). J. Roy. Statist. Soc. Ser. B 54 41-81.
-
(1992)
J. Roy. Statist. Soc. Ser.
, vol.54 B
, pp. 41-81
-
-
Donoho, D.L.1
Johnstone, I.M.2
Hoch, J.C.3
Stern, A.S.4
-
12
-
-
80053264999
-
How biased is the apparent error of a prediction rule?
-
EFRON, B. (1986). How biased is the apparent error of a prediction rule? J. Amer. Statist. Assoc. 81 461-470.
-
(1986)
J. Amer. Statist. Assoc.
, vol.81
, pp. 461-470
-
-
Efron, B.1
-
13
-
-
3242708140
-
Least angle regression (with discussion)
-
EFRON, B., HASTIE, T., JOHNSTONE, I. and TIBSHIRANI, R. (2004). Least angle regression (with discussion). Ann. Statist. 32 407-499.
-
(2004)
Ann. Statist.
, vol.32
, pp. 407-499
-
-
Efron, B.1
Hastie, T.2
Johnstone, I.3
Tibshirani, R.4
-
14
-
-
50849131900
-
Discussion: The Dantzig selector: Statistical estimation when p is much larger than n.
-
EFRON, B., HASTIE, T. and TIBSHIRANI, R. (2007). Discussion: The Dantzig selector: Statistical estimation when p is much larger than n. Ann. Statist. 35 2358-2364.
-
(2007)
Ann. Statist.
, vol.35
, pp. 2358-2364
-
-
Efron, B.1
Hastie, T.2
Tibshirani, R.3
-
15
-
-
0009935552
-
Comments on "wavelets in statistics: A review"
-
by A. Antoniadis
-
FAN, J. (1997). Comments on "Wavelets in statistics: A review" by A. Antoniadis. J. Italian Statist. Assoc. 6 131-138.
-
(1997)
J. Italian Statist. Assoc.
, vol.6
, pp. 131-138
-
-
Fan, J.1
-
16
-
-
1542784498
-
Variable selection via nonconcave penalized likelihood and its oracle properties
-
FAN, J. and LI, R. (2001). Variable selection via nonconcave penalized likelihood and its oracle properties. J. Amer. Statist. Assoc. 96 1348-1360.
-
(2001)
J. Amer. Statist. Assoc.
, vol.96
, pp. 1348-1360
-
-
Fan, J.1
Li, R.2
-
17
-
-
53849086824
-
Sure independence screening for ultrahigh-dimensional feature space
-
FAN, J. and LV, JINCHI. (2008). Sure independence screening for ultrahigh-dimensional feature space. J. Roy. Statist. Soc. Ser. B 70 849-911.
-
(2008)
J. Roy. Statist. Soc. Ser.
, vol.B 70
, pp. 849-911
-
-
Fan, J.1
Jinchi, L.V.2
-
18
-
-
24344502730
-
On nonconcave penalized likelihood with diverging number of parameters
-
FAN, J. and PENG, H. (2004). On nonconcave penalized likelihood with diverging number of parameters. Ann. Statist. 32 928-961.
-
(2004)
Ann. Statist.
, vol.32
, pp. 928-961
-
-
Fan, J.1
Peng, H.2
-
19
-
-
21844523862
-
The risk inflation criterion for multiple regression
-
FOSTER, D. P. and GEORGE, E. I. (1994). The risk inflation criterion for multiple regression. Ann. Statist. 22 1947-1975. MR1329177
-
(1994)
Ann. Statist.
, vol.22
, pp. 1947-1975
-
-
Foster, D.P.1
George, E.I.2
-
21
-
-
0034164230
-
Additive logistic regression: A statistical view of boosting (with discussion)
-
FRIEDMAN, J., HASTIE, T. and TIBSHIRANI, R. (2000). Additive logistic regression: A statistical view of boosting (with discussion). Ann. Statist. 28 337-1307.
-
(2000)
Ann. Statist.
, vol.28
, pp. 337-1307
-
-
Friedman, J.1
Hastie, T.2
Tibshirani, R.3
-
22
-
-
0031312521
-
Waveshrink with firm shrinkage
-
GAO, H.-Y. and BRUCE, A. G. (1997). Waveshrink with firm shrinkage. Statist. Sinica 7 855-874.
-
(1997)
Statist. Sinica
, vol.7
, pp. 855-874
-
-
Gao, H.-Y.1
Bruce, A.G.2
-
23
-
-
8744251722
-
Large-scale Bayesian logistic regression for text categorization
-
Rutgers Univ.
-
GENKIN, A. LEWIS, D. D. andMADIGAN, D. (2004). Large-scale Bayesian logistic regression for text categorization. Technical report, DIMACS, Rutgers Univ.
-
(2004)
Technical Report, DIMACS
-
-
Genkin, A.1
Lewis, D.D.2
Madigan, D.3
-
24
-
-
31344454903
-
Persistence in high-dimensional linear predictor selection and the virtue of overparametrization
-
GREENSHTEIN E. and RITOV Y. (2004). Persistence in high-dimensional linear predictor selection and the virtue of overparametrization. Bernoulli 10 971-988.
-
(2004)
Bernoulli
, vol.10
, pp. 971-988
-
-
Greenshtein, E.1
Ritov, Y.2
-
25
-
-
51049096710
-
Adaptive Lasso for sparse high-dimensional regression models
-
HUANG, J.,MA, S. and ZHANG, C.-H. (2008). Adaptive Lasso for sparse high-dimensional regression models. Statist. Sinica 18 1603-1618.
-
(2008)
Statist. Sinica
, vol.18
, pp. 1603-1618
-
-
Huang, J.1
Ma, S.2
Zhang, C.-H.3
-
26
-
-
26444617168
-
Variable selection using MM algorithms
-
HUNTER, D. R. and LI, R. (2005). Variable selection using MM algorithms. Ann. Statist. 33 1617-1642.
-
(2005)
Ann. Statist.
, vol.33
, pp. 1617-1642
-
-
Hunter, D.R.1
Li, R.2
-
27
-
-
84915425007
-
Some comments on Cp.
-
MALLOWS, C. L. (1973). Some comments on Cp. Technometrics 12 661-675.
-
(1973)
Technometrics
, vol.12
, pp. 661-675
-
-
Mallows, C.L.1
-
29
-
-
33747163541
-
High-dimensional graphs and variable selection with the lasso
-
MEINSHAUSEN, N. and BUHLMANN, P. (2006). High-dimensional graphs and variable selection with the Lasso. Ann. Statist. 34 1436-1462.
-
(2006)
Ann. Statist.
, vol.34
, pp. 1436-1462
-
-
Meinshausen, N.1
Buhlmann, P.2
-
30
-
-
50849120401
-
Discussion: The dantzig selector: Statistical estimation when p is much larger than
-
MEINSHAUSEN, N., ROCHA, G. and YU, B. (2007). Discussion: The Dantzig selector: Statistical estimation when p is much larger than n. Ann. Statist. 35 2373-2384.
-
(2007)
N. Ann. Statist.
, vol.35
, pp. 2373-2384
-
-
Meinshausen, N.1
Rocha, G.2
Yu, B.3
-
31
-
-
65349193793
-
Lasso-type recovery of sparse representations for highdimensional data
-
MEINSHAUSEN, N. and YU, B. (2009). Lasso-type recovery of sparse representations for highdimensional data. Ann. Statist. 37 2246-2270.
-
(2009)
Ann. Statist.
, vol.37
, pp. 2246-2270
-
-
Meinshausen, N.1
Yu, B.2
-
32
-
-
0034237944
-
On the degrees of freedom in shape-restricted regression
-
MEYER, M. andWOODROOFE, M. (2000). On the degrees of freedom in shape-restricted regression. Ann. Statist. 28 1083-1104.
-
(2000)
Ann. Statist.
, Issue.28
, pp. 1083-1104
-
-
Meyer, M.1
Woodroofe, M.2
-
33
-
-
0034215549
-
A new approach to variable selection in least squares problems
-
OSBORNE, M., PRESNELL, B. and TURLACH, B. (2000a). A new approach to variable selection in least squares problems. IMA J. Numer. Anal. 20 389-404.
-
(2000)
IMA J. Numer. Anal.
, vol.20
, pp. 389-404
-
-
Osborne, M.1
Presnell, B.2
Turlach, B.3
-
35
-
-
34547849507
-
An L1 regularization-path algorithm for generalized linear models
-
PARK, M. Y. and HASTIE, T. (2007). An L1 regularization-path algorithm for generalized linear models. J. R. Stat. Soc. Ser. B Stat. Methodol. 69 659-677.
-
(2007)
J. R. Stat. Soc. Ser. B Stat. Methodol.
, vol.69
, pp. 659-677
-
-
Park, M.Y.1
Hastie, T.2
-
36
-
-
34548452938
-
Piecewise linear regularized solution paths
-
ROSSET, S. and ZHU, J. (2007). Piecewise linear regularized solution paths. Ann. Statist. 35 1012-1030.
-
(2007)
Ann. Statist.
, vol.35
, pp. 1012-1030
-
-
Rosset, S.1
Zhu, J.2
-
37
-
-
0025448521
-
The strength of weak learnability
-
SCHAPIRE, R. E. (1990). The strength of weak learnability. Machine Learning 5 197-227.
-
(1990)
Machine Learning
, vol.5
, pp. 197-227
-
-
Schapire, R.E.1
-
38
-
-
0000120766
-
Estimating the dimension of a model
-
SCHWARZ, G. (1978). Estimating the dimension of a model. Ann. Statist. 6 461-464.
-
(1978)
Ann. Statist.
, vol.6
, pp. 461-464
-
-
Schwarz, G.1
-
39
-
-
0000169918
-
Estimation of the mean of a multivariate normal distribution
-
STEIN, C. (1981). Estimation of the mean of a multivariate normal distribution. Ann. Statist. 9 1135-1151. MR0630098
-
(1981)
Ann. Statist.
, vol.9
, pp. 1135-1151
-
-
Stein, C.1
-
40
-
-
0001287271
-
Regression shrinkage and selection via the Lasso
-
TIBSHIRANI, R. (1996). Regression shrinkage and selection via the Lasso. J. Roy. Statist. Soc. Ser. B 58 267-288. MR1379242
-
(1996)
J. Roy. Statist. Soc. Ser. B
, vol.58
, pp. 267-288
-
-
Tibshirani, R.1
-
41
-
-
33645712308
-
Just relax: Convex programming methods for identifying sparse signals in noise]
-
TROPP, J. A. (2006). Just relax: Convex programming methods for identifying sparse signals in noise. IEEE Trans. Inform. Theory 52 1030-1051.
-
(2006)
IEEE Trans. Inform. Theory
, vol.52
, pp. 1030-1051
-
-
Tropp, J.A.1
-
42
-
-
51049121146
-
High-dimensional generalized linear models and the Lasso
-
VAN DE GEER, S. (2008). High-dimensional generalized linear models and the Lasso. Ann. Statist. 36 614-645.
-
(2008)
Ann. Statist.
, vol.36
, pp. 614-645
-
-
Van De Geer, S.1
-
43
-
-
41949129774
-
Sharp thresholds for high-dimensional and noisy recovery of sparsity
-
Dept. Statistics, Univ. California, Berkeley.
-
WAINWRIGHT, M. (2006). Sharp thresholds for high-dimensional and noisy recovery of sparsity. Technical Report 708, Dept. Statistics, Univ. California, Berkeley.
-
(2006)
Technical Report 708
-
-
Wainwright, M.1
-
44
-
-
77649278149
-
Rate minimaxity of the lasso and dantzig estimators
-
Dept. Statistics, Rutgers Univ.
-
YE, F. and ZHANG, C.-H. (2009). Rate Minimaxity of the Lasso and Dantzig Estimators. Technical Report No. 2009-3001 Dept. Statistics, Rutgers Univ.
-
(2009)
Technical Report No. 2009-3001
-
-
Ye, F.1
Zhang, C.-H.2
-
46
-
-
38049113238
-
Continuous generalized gradient descent
-
ZHANG, C.-H. (2007a). Continuous generalized gradient descent. J. Comput. Graph. Statist. 16 761-781.
-
(2007)
J. Comput. Graph. Statist.
, vol.16
, pp. 761-781
-
-
Zhang, C.-H.1
-
47
-
-
51049092645
-
Penalized linear unbiased selection
-
Dept. Statistics, Rutgers Univ.
-
ZHANG, C.-H. (2007b). Penalized linear unbiased selection. Technical Report 2007-3003 Dept. Statistics, Rutgers Univ.
-
(2007)
Technical Report 2007-3003
-
-
Zhang, C.-H.1
-
48
-
-
77649330357
-
Information-theoretic optimality of variable selection with concave penalty
-
Dept. Statistics, Rutgers Univ.
-
ZHANG, C.-H. (2007c). Information-theoretic optimality of variable selection with concave penalty. Technical Report No. 2007-2008 Dept. Statistics, Rutgers Univ.
-
(2007)
Technical Report No. 2007-2008
-
-
Zhang, C.-H.1
-
49
-
-
51049101956
-
Discussion: One-step sparse estimates in nonconcave penalized likelihood models
-
ZHANG, C.-H. (2008). Discussion: One-step sparse estimates in nonconcave penalized likelihood models. Ann. Statist. 36 1553-1560.
-
(2008)
Ann. Statist.
, vol.36
, pp. 1553-1560
-
-
Zhang, C.-H.1
-
50
-
-
50949096321
-
The sparsity and bias of the LASSO selection in highdimensional regression
-
ZHANG, C.-H. and HUANG, J. (2008). The sparsity and bias of the LASSO selection in highdimensional regression. Ann. Statist. 36 1567-1594.
-
(2008)
Ann. Statist.
, vol.36
, pp. 1567-1594
-
-
Zhang, C.-H.1
Huang, J.2
-
51
-
-
33845263263
-
On model selection consistency of LASSO
-
ZHAO, P. and YU, B. (2006). On model selection consistency of LASSO. J. Mach. Learn. Res. 7 2541-2567.
-
(2006)
J. Mach. Learn. Res.
, vol.7
, pp. 2541-2567
-
-
Zhao, P.1
Yu, B.2
-
53
-
-
33846114377
-
The adaptive Lasso and its oracle properties
-
ZOU, H. (2006). The adaptive Lasso and its oracle properties. J. Amer. Statist. Assoc. 101 1418-1429.
-
(2006)
J. Amer. Statist. Assoc.
, vol.101
, pp. 1418-1429
-
-
Zou, H.1
-
54
-
-
51049104549
-
One-step sparse estimates in nonconcave penalized likelihood models (with discussion)
-
ZOU, H. and LI, R. (2008). One-step sparse estimates in nonconcave penalized likelihood models (with discussion). Ann. Statist. 36 1509-1533.
-
(2008)
Ann. Statist.
, vol.36
, pp. 1509-1533
-
-
Zou, H.1
Li, R.2
|