-
1
-
-
85014561619
-
A fast iterative shrinkage-thresholding algorithm for linear inverse problems
-
MR2486527
-
BECK, A. and TEBOULLE, M. (2009). A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci. 2 183-202. MR2486527
-
(2009)
SIAM J. Imaging Sci.
, vol.2
, pp. 183-202
-
-
Beck, A.1
Teboulle, M.2
-
2
-
-
79551550744
-
NESTA: A fast and accurate first-order method for sparse recovery
-
MR2765668
-
BECKER, S., BOBIN, J. and CANDÈS, E. J. (2011). NESTA: A fast and accurate first-order method for sparse recovery. SIAM J. Imaging Sci. 4 1-39. MR2765668
-
(2011)
SIAM J. Imaging Sci.
, vol.4
, pp. 1-39
-
-
Becker, S.1
Bobin, J.2
Candès, E.J.3
-
3
-
-
84856004485
-
Templates for convex cone problems with applications to sparse signal recovery
-
MR2833262
-
BECKER, S. R., CANDÈS, E. J. and GRANT, M. C. (2011). Templates for convex cone problems with applications to sparse signal recovery. Math. Program. Comput. 3 165-218. MR2833262
-
(2011)
Math. Program. Comput.
, vol.3
, pp. 165-218
-
-
Becker, S.R.1
Candès, E.J.2
Grant, M.C.3
-
4
-
-
80051762104
-
Distributed optimization and statistical learning via the alternative direction method of multipliers
-
BOYD, S., PARIKH, N., CHU, E., PELEATO, B. and ECKSTEIN, J. (2011). Distributed optimization and statistical learning via the alternative direction method of multipliers. Faund. Trends Mach. Learn. 3 1-122.
-
(2011)
Faund. Trends Mach. Learn.
, vol.3
, pp. 1-122
-
-
Boyd, S.1
Parikh, N.2
Chu, E.3
Peleato, B.4
Eckstein, J.5
-
5
-
-
84885049881
-
Statistical significance in high-dimensional linear models
-
MR3102549
-
BÜHLMANN, P. (2013). Statistical significance in high-dimensional linear models. Bernoulli 19 1212-1242. MR3102549
-
(2013)
Bernoulli
, vol.19
, pp. 1212-1242
-
-
Bühlmann, P.1
-
6
-
-
69049120308
-
Near-ideal model selection by ℓ1 minimization
-
MR2543688
-
CANDÈS, E. J. and PLAN, Y. (2009). Near-ideal model selection by ℓ1 minimization. Ann. Statist. 37 2145-2177. MR2543688
-
(2009)
Ann. Statist.
, vol.37
, pp. 2145-2177
-
-
Candès, E.J.1
Plan, Y.2
-
7
-
-
33947416035
-
Near-optimal signal recovery from random projections: Universal encoding strategies?
-
MR2300700
-
CANDES, E. J. and TAO, T. (2006). Near-optimal signal recovery from random projections: Universal encoding strategies? IEEE Trans. Inform. Theory 52 5406-5425. MR2300700
-
(2006)
IEEE Trans. Inform. Theory
, vol.52
, pp. 5406-5425
-
-
Candes, E.J.1
Tao, T.2
-
10
-
-
33645712892
-
Compressed sensing
-
MR2241189
-
DONOHO, D. L. (2006). Compressed sensing. IEEE Trans. Inform. Theory 52 1289-1306. MR2241189
-
(2006)
IEEE Trans. Inform. Theory
, vol.52
, pp. 1289-1306
-
-
Donoho, D.L.1
-
11
-
-
80053264999
-
How biased is the apparent error rate of a prediction rule?
-
MR0845884
-
EFRON, B. (1986). How biased is the apparent error rate of a prediction rule? J. Amer. Statist. Assoc. 81 461-470. MR0845884
-
(1986)
J. Amer. Statist. Assoc.
, vol.81
, pp. 461-470
-
-
Efron, B.1
-
12
-
-
3242708140
-
Least angle regression
-
MR2060166
-
EFRON, B., HASTIE, T., JOHNSTONE, I. and TIBSHIRANI, R. (2004). Least angle regression. Ann. Statist. 32 407-499. MR2060166
-
(2004)
Ann. Statist.
, vol.32
, pp. 407-499
-
-
Efron, B.1
Hastie, T.2
Johnstone, I.3
Tibshirani, R.4
-
13
-
-
84855983910
-
Variance estimation using refitted cross-validation in ultrahigh-dimensional regression
-
MR2885839
-
FAN, J., GUO, S. and HAO, N. (2012). Variance estimation using refitted cross-validation in ultrahigh-dimensional regression. J. R. Stat. Soc. Ser. B Stat. Methodol. 74 37-65. MR2885839
-
(2012)
J. R. Stat. Soc. Ser. B Stat. Methodol.
, vol.74
, pp. 37-65
-
-
Fan, J.1
Guo, S.2
Hao, N.3
-
14
-
-
77950537175
-
Regularization paths for generalized linear models via coordinate descent
-
FRIEDMAN, J., HASTIE, T. and TIBSHIRANI, R. (2010). Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33 1-22.
-
(2010)
J. Stat. Softw.
, vol.33
, pp. 1-22
-
-
Friedman, J.1
Hastie, T.2
Tibshirani, R.3
-
15
-
-
45849107328
-
Pathwise coordinate optimization
-
MR2415737
-
FRIEDMAN, J., HASTIE, T., HÖFLING, H. and TIBSHIRANI, R. (2007). Pathwise coordinate optimization. Ann. Appl. Stat. 1 302-332. MR2415737
-
(2007)
Ann. Appl. Stat.
, vol.1
, pp. 302-332
-
-
Friedman, J.1
Hastie, T.2
Höfling, H.3
Tibshirani, R.4
-
16
-
-
26844461512
-
Recovery of exact sparse representations in the presence of bounded noise
-
MR2237526
-
FUCHS, J. J. (2005). Recovery of exact sparse representations in the presence of bounded noise. IEEE Trans. Inform. Theory 51 3601-3608. MR2237526
-
(2005)
IEEE Trans. Inform. Theory
, vol.51
, pp. 3601-3608
-
-
Fuchs, J.J.1
-
18
-
-
84901699785
-
-
Preprint. Available at arXiv: 1309.5352
-
GRAZIER G'SELL, M., WAGER, S., CHOULDECHOVA, A. and TIBSHIRANI, R. (2013). False discovery rate control for sequential selection procedures, with application to the lasso. Preprint. Available at arXiv:1309.5352.
-
(2013)
False Discovery Rate Control for Sequential Selection Procedures, with Application to the Lasso
-
-
Grazier G'Sell, M.1
Wager, S.2
Chouldechova, A.3
Tibshirani, R.4
-
19
-
-
31344454903
-
Persistence in high-dimensional linear predictor selection and the virtue of overparametrization
-
MR2108039
-
GREENSHTEIN, E. and RITOV, Y. (2004). Persistence in high-dimensional linear predictor selection and the virtue of overparametrization. Bernoulli 10 971-988. MR2108039
-
(2004)
Bernoulli
, vol.10
, pp. 971-988
-
-
Greenshtein, E.1
Ritov, Y.2
-
20
-
-
0003684449
-
-
Springer, New York. MR2722294
-
HASTIE, T., TIBSHIRANI, R. and FRIEDMAN, J. (2008). The Elements of Statistical Learning; Data Mining, Inference, and Prediction, 2nd ed. Springer, New York. MR2722294
-
(2008)
The Elements of Statistical Learning; Data Mining, Inference, and Prediction, 2nd Ed
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.3
-
25
-
-
84855997958
-
A perturbation method for inference on regularized regression estimates
-
MR2896842
-
MINNIER, J., TIAN, L. and CAI, T. (2011). A perturbation method for inference on regularized regression estimates. J. Amer. Statist. Assoc. 106 1371-1382. MR2896842
-
(2011)
J. Amer. Statist. Assoc.
, vol.106
, pp. 1371-1382
-
-
Minnier, J.1
Tian, L.2
Cai, T.3
-
26
-
-
0034215549
-
A new approach to variable selection in least squares problems
-
MR1773265
-
OSBORNE, M. R., PRESNELL, B. and TURLACH, B. A. (2000a). A new approach to variable selection in least squares problems. IMA J. Numer. Anal. 20 389-403. MR1773265
-
(2000)
IMA J. Numer. Anal.
, vol.20
, pp. 389-403
-
-
Osborne, M.R.1
Presnell, B.2
Turlach, B.A.3
-
28
-
-
34547849507
-
L1-regularization path algorithm for generalized linear models
-
MR2370074
-
PARK, M. Y. and HASTIE, T. (2007). L1-regularization path algorithm for generalized linear models. J. R. Stat. Soc. Ser. B Stat. Methodol. 69 659-677. MR2370074
-
(2007)
J. R. Stat. Soc. Ser. B Stat. Methodol.
, vol.69
, pp. 659-677
-
-
Park, M.Y.1
Hastie, T.2
-
29
-
-
0037250521
-
Human immunodeficiency virus reverse transcriptase and protease sequence database
-
DOI 10.1093/nar/gkg100
-
RHEE, S.-Y., GONZALES, M. J., KANTOR, R., BETTS, B. J., RAVELA, J. and SHAFER, R. W. (2003). Human immunodeficiency virus reverse transcriptase and protease sequence database. Nucleic Acids Res. 31 298-303. (Pubitemid 36150389)
-
(2003)
Nucleic Acids Research
, vol.31
, Issue.1
, pp. 298-303
-
-
Rhee, S.-Y.1
Gonzales, M.J.2
Kantor, R.3
Betts, B.J.4
Ravela, J.5
Shafer, R.W.6
-
30
-
-
84869449202
-
Scaled sparse linear regression
-
MR2999166
-
SUN, T. and ZHANG, C.-H. (2012). Scaled sparse linear regression. Biometrika 99 879-898. MR2999166
-
(2012)
Biometrika
, vol.99
, pp. 879-898
-
-
Sun, T.1
Zhang, C.-H.2
-
32
-
-
23244455084
-
Validity of the expected Euler characteristic heuristic
-
MR2150192
-
TAYLOR, J., TAKEMURA, A. andADLER, R. J. (2005). Validity of the expected Euler characteristic heuristic. Ann. Probab. 33 1362-1396. MR2150192
-
(2005)
Ann. Probab.
, vol.33
, pp. 1362-1396
-
-
Taylor, J.1
Takemura, A.2
Adler, R.J.3
-
33
-
-
85194972808
-
Regression shrinkage and selection via the lasso
-
MR1379242
-
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
-
34
-
-
84884951589
-
The lasso problem and uniqueness
-
MR3066375
-
TIBSHIRANI, RYAN J. (2013). The lasso problem and uniqueness. Electron. J. Stat. 7 1456-1490. MR3066375
-
(2013)
Electron. J. Stat.
, vol.7
, pp. 1456-1490
-
-
Tibshirani Ryan, J.1
-
35
-
-
84872012577
-
Degrees of freedom in lasso problems
-
MR2985948
-
TIBSHIRANI, R. J. and TAYLOR, J. (2012). Degrees of freedom in lasso problems. Ann. Statist. 40 1198-1232. MR2985948
-
(2012)
Ann. Statist.
, vol.40
, pp. 1198-1232
-
-
Tibshirani, R.J.1
Taylor, J.2
-
37
-
-
65749083666
-
Sharp thresholds for high-dimensional and noisy sparsity recovery using ℓ1-constrained quadratic programming (Lasso)
-
MR2729873
-
WAINWRIGHT, M. J. (2009). Sharp thresholds for high-dimensional and noisy sparsity recovery using ℓ1-constrained quadratic programming (Lasso). IEEE Trans. Inform. Theory 55 2183-2202. MR2729873
-
(2009)
IEEE Trans. Inform. Theory
, vol.55
, pp. 2183-2202
-
-
Wainwright, M.J.1
-
38
-
-
69049091975
-
High-dimensional variable selection
-
MR2543689
-
WASSERMAN, L. and ROEDER, K. (2009). High-dimensional variable selection. Ann. Statist. 37 2178-2201. MR2543689
-
(2009)
Ann. Statist.
, vol.37
, pp. 2178-2201
-
-
Wasserman, L.1
Roeder, K.2
-
39
-
-
84936167519
-
Estimation of parameters and large quantiles based on the k largest observations
-
MR0521329
-
WEISSMAN, I. (1978). Estimation of parameters and large quantiles based on the k largest observations. J. Amer. Statist. Assoc. 73 812-815. MR0521329
-
(1978)
J. Amer. Statist. Assoc.
, vol.73
, pp. 812-815
-
-
Weissman, I.1
-
40
-
-
84891835103
-
Confidence intervals for low dimensional parameters in high dimensional linear models
-
MR3153940
-
ZHANG, C.-H. and ZHANG, S. (2014). Confidence intervals for low dimensional parameters in high dimensional linear models. J. R. Stat. Soc. Ser. B Stat. Methodol. 76 217-242. MR3153940
-
(2014)
J. R. Stat. Soc. Ser. B Stat. Methodol.
, vol.76
, pp. 217-242
-
-
Zhang, C.-H.1
Zhang, S.2
-
41
-
-
33845263263
-
On model selection consistency of Lasso
-
MR2274449
-
ZHAO, P. and YU, B. (2006). On model selection consistency of Lasso. J. Mach. Learn. Res. 7 2541-2563. MR2274449
-
(2006)
J. Mach. Learn. Res.
, vol.7
, pp. 2541-2563
-
-
Zhao, P.1
Yu, B.2
-
42
-
-
16244401458
-
Regularization and variable selection via the elastic net
-
MR2137327
-
ZOU, H. and HASTIE, T. (2005). Regularization and variable selection via the elastic net. J. R. Stat. Soc. Ser. B Stat. Methodol. 67 301-320. MR2137327
-
(2005)
J. R. Stat. Soc. Ser. B Stat. Methodol.
, vol.67
, pp. 301-320
-
-
Zou, H.1
Hastie, T.2
-
43
-
-
34548536008
-
On the "degrees of freedom" of the lasso
-
MR2363967
-
ZOU, H., HASTIE, T. and TIBSHIRANI, R. (2007). On the "degrees of freedom" of the lasso. Ann. Statist. 35 2173-2192. MR2363967
-
(2007)
Ann. Statist.
, vol.35
, pp. 2173-2192
-
-
Zou, H.1
Hastie, T.2
Tibshirani, R.3
|