-
1
-
-
84860244324
-
Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization
-
A. Agarwal, P. L. Bartlett, P. Ravikumar, and M. J. Wainwright. Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization. IEEE Transactions on Information Theory, 58(5):3235–3249, 2012.
-
(2012)
IEEE Transactions on Information Theory
, vol.58
, Issue.5
, pp. 3235-3249
-
-
Agarwal, A.1
Bartlett, P.L.2
Ravikumar, P.3
Wainwright, M.J.4
-
3
-
-
84877750537
-
Stochastic convex optimization with bandit feedback
-
A. Agarwal, D. Foster, D. Hsu, S. Kakade, and A. Rakhlin. Stochastic convex optimization with bandit feedback. SIAM Journal on Optimization, 23(1):213–240, 2013.
-
(2013)
SIAM Journal on Optimization
, vol.23
, Issue.1
, pp. 213-240
-
-
Agarwal, A.1
Foster, D.2
Hsu, D.3
Kakade, S.4
Rakhlin, A.5
-
4
-
-
84865690792
-
Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization
-
A. S. Bandeira, K. Scheinberg, and L. N. Vicente. Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization. Mathematical Programming, 134:223–257, 2012.
-
(2012)
Mathematical Programming
, vol.134
, pp. 223-257
-
-
Bandeira, A.S.1
Scheinberg, K.2
Vicente, L.N.3
-
5
-
-
84910601452
-
Convergence of trust-region methods based on probabilistic models
-
A. S. Bandeira, K. Scheinberg, and L. N. Vicente. Convergence of trust-region methods based on probabilistic models. SIAM Journal on Optimization, 24(3):1238–1264, 2014.
-
(2014)
SIAM Journal on Optimization
, vol.24
, Issue.3
, pp. 1238-1264
-
-
Bandeira, A.S.1
Scheinberg, K.2
Vicente, L.N.3
-
6
-
-
0037403111
-
Mirror descent and nonlinear projected subgradient methods for convex optimization
-
A. Beck and M. Teboulle. Mirror descent and nonlinear projected subgradient methods for convex optimization. Operations Research Letters, 31(3):167–175, 2003.
-
(2003)
Operations Research Letters
, vol.31
, Issue.3
, pp. 167-175
-
-
Beck, A.1
Teboulle, M.2
-
7
-
-
68649086910
-
Simultaneous analysis of lasso and dantzig selector
-
P. J. Bickel, Y. Ritov, and A. B. Tsybakov. Simultaneous analysis of lasso and dantzig selector. The Annals of Statistics, 37(4):1705–1732, 2009.
-
(2009)
The Annals of Statistics
, vol.37
, Issue.4
, pp. 1705-1732
-
-
Bickel, P.J.1
Ritov, Y.2
Tsybakov, A.B.3
-
9
-
-
80555140070
-
Convergence rates of efficient global optimization algorithms
-
A. D. Bull. Convergence rates of efficient global optimization algorithms. Journal of Machine Learning Research, 12(Oct):2879–2904, 2011.
-
(2011)
Journal of Machine Learning Research
, vol.12
, Issue.Oct
, pp. 2879-2904
-
-
Bull, A.D.1
-
10
-
-
31744440684
-
Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
-
E. J. Candès, J. Romberg, and T. Tao. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Information Theory, 52(2):489–509, 2006.
-
(2006)
IEEE Transactions on Information Theory
, vol.52
, Issue.2
, pp. 489-509
-
-
Candès, E.J.1
Romberg, J.2
Tao, T.3
-
14
-
-
84871576447
-
Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization I: A generic algorithmic framework
-
S. Ghadimi and G. Lan. Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization I: A generic algorithmic framework. SIAM Journal on Optimization, 22(4):1469–1492, 2012.
-
(2012)
SIAM Journal on Optimization
, vol.22
, Issue.4
, pp. 1469-1492
-
-
Ghadimi, S.1
Lan, G.2
-
15
-
-
84892856128
-
Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization, II: Shrinking procedures and optimal algorithms
-
S. Ghadimi and G. Lan. Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization, II: shrinking procedures and optimal algorithms. SIAM Journal on Optimization, 23(4):2061–2089, 2013.
-
(2013)
SIAM Journal on Optimization
, vol.23
, Issue.4
, pp. 2061-2089
-
-
Ghadimi, S.1
Lan, G.2
-
17
-
-
84947403595
-
Probability inequalities for sums of bounded random variables
-
W. Hoeffding. Probability inequalities for sums of bounded random variables. Journal of the American Statistical Association, 58(301):13–30, 1963.
-
(1963)
Journal of the American Statistical Association
, vol.58
, Issue.301
, pp. 13-30
-
-
Hoeffding, W.1
-
19
-
-
84919709419
-
Confidence intervals and hypothesis testing for high-dimensional regression
-
A. Javanmard and A. Montanari. Confidence intervals and hypothesis testing for high-dimensional regression. Journal of Machine Learning Research, 15(1):2869–2909, 2014.
-
(2014)
Journal of Machine Learning Research
, vol.15
, Issue.1
, pp. 2869-2909
-
-
Javanmard, A.1
Montanari, A.2
-
21
-
-
0034287156
-
Asymptotics for lasso-type estimators
-
K. Knight and W. Fu. Asymptotics for lasso-type estimators. The Annals of statistics, 28(5):1356–1378, 2000.
-
(2000)
The Annals of Statistics
, vol.28
, Issue.5
, pp. 1356-1378
-
-
Knight, K.1
Fu, W.2
-
22
-
-
84862273593
-
An optimal method for stochastic composite optimization
-
G. Lan. An optimal method for stochastic composite optimization. Mathematical Programming, 133:365–397, 2012.
-
(2012)
Mathematical Programming
, vol.133
, pp. 365-397
-
-
Lan, G.1
-
24
-
-
85048511868
-
Doubly greedy primal-dual coordinate descent for sparse empirical risk minimization
-
Q. Lei, I. E.-H. Yen, C.-y. Wu, I. S. Dhillon, and P. Ravikumar. Doubly greedy primal-dual coordinate descent for sparse empirical risk minimization. In Proceedings of the International Conference on Machine Learning (ICML), 2017.
-
(2017)
Proceedings of the International Conference on Machine Learning (ICML)
-
-
Lei, Q.1
Yen, I.E.-H.2
Wu, C.-Y.3
Dhillon, I.S.4
Ravikumar, P.5
-
25
-
-
56449113372
-
Sup-norm convergence rate and sign concentration property of lasso and dantzig estimators
-
K. Lounici. Sup-norm convergence rate and sign concentration property of lasso and dantzig estimators. Electronic Journal of Statistics, 2:90–102, 2008.
-
(2008)
Electronic Journal of Statistics
, vol.2
, pp. 90-102
-
-
Lounici, K.1
-
27
-
-
70450197241
-
Robust stochastic approximation approach to stochastic programming
-
A. Nemirovski, A. Juditsky, G. Lan, and A. Shapiro. Robust stochastic approximation approach to stochastic programming. SIAM Journal on Optimization, 19(4):1574–1609, 2009.
-
(2009)
SIAM Journal on Optimization
, vol.19
, Issue.4
, pp. 1574-1609
-
-
Nemirovski, A.1
Juditsky, A.2
Lan, G.3
Shapiro, A.4
-
29
-
-
2642531109
-
Twicing kernels and a small bias property of semiparametric estimators
-
W. K. Newey, F. Hsieh, and J. M. Robins. Twicing kernels and a small bias property of semiparametric estimators. Econometrica, 72(3):947–962, 2004.
-
(2004)
Econometrica
, vol.72
, Issue.3
, pp. 947-962
-
-
Newey, W.K.1
Hsieh, F.2
Robins, J.M.3
-
30
-
-
80053974183
-
Mini-max rates of estimation for high-dimensional linear regression over lq-balls
-
G. Raskutti, M. J. Wainwright, and B. Yu. Mini-max rates of estimation for high-dimensional linear regression over Lq-balls. IEEE Transactions on Information Theory, 57(10):6976–6994, 2011.
-
(2011)
IEEE Transactions on Information Theory
, vol.57
, Issue.10
, pp. 6976-6994
-
-
Raskutti, G.1
Wainwright, M.J.2
Yu, B.3
-
31
-
-
84871783096
-
Microwave-assisted low-temperature growth of thin films in solution
-
B. Reeja-Jayan, K. L. Harrison, K. Yang, C.-L. Wang, A. Yilmaz, and A. Manthiram. Microwave-assisted low-temperature growth of thin films in solution. Scientific reports, 2, 2012.
-
(2012)
Scientific Reports
, vol.2
-
-
Reeja-Jayan, B.1
Harrison, K.L.2
Yang, K.3
Wang, C.-L.4
Yilmaz, A.5
Manthiram, A.6
-
33
-
-
79251503629
-
Trading accuracy for sparsity in optimization problems with sparsity constraints
-
S. Shalev-Shwartz, N. Srebro, and T. Zhang. Trading accuracy for sparsity in optimization problems with sparsity constraints. SIAM Journal on Optimization, 20(6):2807–2832, 2010.
-
(2010)
SIAM Journal on Optimization
, vol.20
, Issue.6
, pp. 2807-2832
-
-
Shalev-Shwartz, S.1
Srebro, N.2
Zhang, T.3
-
34
-
-
79960131832
-
Stochastic methods for l1-regularized loss minimization
-
S. Shalev-Shwartz and A. Tewari. Stochastic methods for l1-regularized loss minimization. Journal of Machine Learning Research, 12(Jun):1865–1892, 2011.
-
(2011)
Journal of Machine Learning Research
, vol.12
, Issue.Jun
, pp. 1865-1892
-
-
Shalev-Shwartz, S.1
Tewari, A.2
-
39
-
-
84988001472
-
On asymptotically optimal confidence regions and tests for high-dimensional models
-
S. Van de Geer, P. Bühlmann, Y. Ritov, R. Dezeure, et al. On asymptotically optimal confidence regions and tests for high-dimensional models. The Annals of Statistics, 42(3):1166–1202, 2014.
-
(2014)
The Annals of Statistics
, vol.42
, Issue.3
, pp. 1166-1202
-
-
Van de Geer, S.1
Bühlmann, P.2
Ritov, Y.3
Dezeure, R.4
-
40
-
-
0032622766
-
A general class of exponential inequalities for martingales and ratios
-
H. Victor. A general class of exponential inequalities for martingales and ratios. The Annals of Probability, 27(1):537–564, 1999.
-
(1999)
The Annals of Probability
, vol.27
, Issue.1
, pp. 537-564
-
-
Victor, H.1
-
41
-
-
65749083666
-
Sharp thresholds for high-dimensional and noisy sparsity recovery using l1-constrained quadratic programming (lasso)
-
M. J. Wainwright. Sharp thresholds for high-dimensional and noisy sparsity recovery using L1-constrained quadratic programming (Lasso). IEEE Transactions on Information T theory, 55(5):2183–2202, 2009.
-
(2009)
IEEE Transactions on Information T Theory
, vol.55
, Issue.5
, pp. 2183-2202
-
-
Wainwright, M.J.1
-
42
-
-
84880741411
-
A proximal-gradient homotopy method for the sparse least-squares problem
-
L. Xiao and T. Zhang. A proximal-gradient homotopy method for the sparse least-squares problem. SIAM Journal on Optimization, 23(2):1062–1091, 2013.
-
(2013)
SIAM Journal on Optimization
, vol.23
, Issue.2
, pp. 1062-1091
-
-
Xiao, L.1
Zhang, T.2
-
44
-
-
33845263263
-
On model selection consistency of lasso
-
P. Zhao and B. Yu. On model selection consistency of lasso. Journal of Machine learning research, 7(Nov):2541–2563, 2006.
-
(2006)
Journal of Machine Learning Research
, vol.7
, Issue.Nov
, pp. 2541-2563
-
-
Zhao, P.1
Yu, B.2
|