-
2
-
-
47649103974
-
Gaussian predictive process models for large spatial data sets
-
BANERJEE, S.,GELFAND, A. E., FINLEY, A. O. & SANG, H. (2008). Gaussian predictive process models for large spatial data sets. J. R. Statist. Soc. B 70, 825-48.
-
(2008)
J. R. Statist. Soc
, vol.70
, pp. 825-848
-
-
Banerjee, S.1
Gelfand, A.E.2
Finley, A.O.3
Sang, H.4
-
4
-
-
31744440684
-
Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
-
CANDES, E. J., ROMBERG, J. & TAO, T. (2006). Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Info. Theory 52, 489-509.
-
(2006)
IEEE Trans. Info. Theory
, vol.52
, pp. 489-509
-
-
Candes, E.J.1
Romberg, J.2
Tao, T.3
-
5
-
-
35348953749
-
On posterior consistency in nonparametric regression problems
-
CHOI, T. & SCHERVISH, M. J. (2007). On posterior consistency in nonparametric regression problems. J. Mult. Anal. 98, 1969-87.
-
(2007)
J. Mult. Anal
, vol.98
, pp. 1969-1987
-
-
Choi, T.1
Schervish, M.J.2
-
6
-
-
37849041594
-
Fixed rank kriging for very large spatial data sets
-
CRESSIE, N. & JOHANNESSON, G. (2008). Fixed rank kriging for very large spatial data sets. J. R. Statist. Soc. B 70, 209-26.
-
(2008)
J. R. Statist. Soc
, vol.70
, pp. 209-226
-
-
Cressie, N.1
Johannesson, G.2
-
7
-
-
0038891993
-
Sparse on-line Gaussian processes
-
CSAT ́O, L. & OPPER, M. (2002). Sparse on-line Gaussian processes. Neural Comp. 14, 641-68.
-
(2002)
Neural Comp
, vol.14
, pp. 641-668
-
-
Csat ́o, L.1
Opper, M.2
-
8
-
-
0037236821
-
An elementary proof of a theorem of Johnson and Lindenstrauss
-
DASGUPTA, S. & GUPTA, A. (2003). An elementary proof of a theorem of Johnson and Lindenstrauss. Random Struct. Algor. 22, 60-5.
-
(2003)
Random Struct. Algor
, vol.22
, pp. 60-65
-
-
Dasgupta, S.1
Gupta, A.2
-
10
-
-
34249922698
-
Unitary similarity of projectors
-
DOKOVI'C, D. (1991). Unitary similarity of projectors. Aequationes Math. 42, 220-4.
-
(1991)
Aequationes Math
, vol.42
, pp. 220-224
-
-
Dokovi'C, D.1
-
12
-
-
29244453931
-
On the Nystr?om method for approximating a Gram matrix for improved kernel-based learning
-
DRINEAS, P. & MAHONEY, M. W. (2005). On the Nystr?om method for approximating a Gram matrix for improved kernel-based learning. J. Mach. Learn. Res. 6, 2153-75.
-
(2005)
J. Mach. Learn. Res
, vol.6
, pp. 2153-2175
-
-
Drineas, P.1
Mahoney, M.W.2
-
13
-
-
62849106305
-
Improving the performance of predictive process modeling for large datasets
-
FINLEY, A. O., SANG, H., BANERJEE, S. & GELFAND, A. E. (2009). Improving the performance of predictive process modeling for large datasets. Comp. Statist. Data Anal. 53, 2873-84.
-
(2009)
Comp. Statist. Data Anal
, vol.53
, pp. 2873-2884
-
-
Finley, A.O.1
Sang, H.2
Banerjee, S.3
Gelfand, A.E.4
-
14
-
-
66549124160
-
Stable and efficient Gaussian process calculations
-
FOSTER, L., WAAGEN, A., AIJAZ, N., HURLEY, M., LUIS, A., RINSKY, J., SATYAVOLU, C., WAY, M. J., GAZIS, P. & SRIVASTAVA, A. (2009). Stable and efficient Gaussian process calculations. J. Mach. Learn. Res. 10, 857-82.
-
(2009)
J. Mach. Learn. Res
, vol.10
, pp. 857-882
-
-
Foster, L.1
Waagen, A.2
Aijaz, N.3
Hurley, M.4
Luis, A.5
Rinsky, J.6
Satyavolu, C.7
Way, M.J.8
Gazis, P.9
Srivastava, A.10
-
16
-
-
10444261986
-
Finite elements for elliptic problems with stochastic coefficients
-
FRAUENFELDER, P., SCHWAB, C. & TODOR, R. A. (2005). Finite elements for elliptic problems with stochastic coefficients. Comp. Meth. Appl. Mech. Eng. 194, 205-28.
-
(2005)
Comp. Meth. Appl. Mech. Eng
, vol.194
, pp. 205-228
-
-
Frauenfelder, P.1
Schwab, C.2
Todor, R.A.3
-
18
-
-
33750049940
-
Bayesian sequential inference for nonlinear multivariate diffusions
-
GOLIGHTLY, A.&WILKINSON, D. J. (2006). Bayesian sequential inference for nonlinear multivariate diffusions. Statist. Comp. 16, 323-38.
-
(2006)
Statist. Comp
, vol.16
, pp. 323-338
-
-
Golightly, A.1
Wilkinson, D.J.2
-
19
-
-
0042645752
-
Stochastic calculus: Applications in science and engineering
-
GRIGORIU, M. (2002). Stochastic Calculus: Applications in Science and Engineering. Boston: Birkh?auser.
-
(2002)
Boston: Birkh?auser
-
-
Grigoriu, M.1
-
20
-
-
83555174652
-
Adaptive Gaussian predictive process models for large spatial datasets
-
GUHANIYOGI, R., FINLEY, A. O., BANERJEE, S. & GELFAND, A. E. (2011). Adaptive Gaussian predictive process models for large spatial datasets. Environmetrics 22, 997-1007.
-
(2011)
Environmetrics
, vol.22
, pp. 997-1007
-
-
Guhaniyogi, R.1
Finley, A.O.2
Banerjee, S.3
Gelfand, A.E.4
-
21
-
-
79960425522
-
Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
-
HALKO, N.,MARTINSSON, P. G. & TROPP, J. A. (2011). Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions. SIAM Rev. 53, 217-88.
-
(2011)
SIAM Rev
, vol.53
, pp. 217-288
-
-
Halko, N.1
Martinsson, P.G.2
Tropp, J.A.3
-
23
-
-
51249179296
-
Extensions of Lipschitz maps into Banach spaces
-
LINDENSTRAUSS, J. & SCHECHTMAN, G. (1986). Extensions of Lipschitz maps into Banach spaces. Israel J. Math. 54, 129-38.
-
(1986)
Israel J. Math
, vol.54
, pp. 129-138
-
-
Lindenstrauss, J.1
Schechtman, G.2
-
24
-
-
84864068501
-
A matching pursuit approach to sparse Gaussian process regression
-
KEERTHI, S. & CHU, W. (2006). A matching pursuit approach to sparse Gaussian process regression. Adv. Neural Info. Proces. Syst. 18, 643-50.
-
(2006)
Adv. Neural Info. Proces. Syst
, vol.18
, pp. 643-650
-
-
Keerthi, S.1
Chu, W.2
-
25
-
-
41149087694
-
CODA: Convergence diagnosis and output analysis for MCMC
-
PLUMMER, M., BEST, N., COWLES, K. & VINES, K. (2006). CODA: Convergence diagnosis and output analysis for MCMC. R News 6, 7-11.
-
(2006)
R News
, vol.6
, pp. 7-11
-
-
Plummer, M.1
Best, N.2
Cowles, K.3
Vines, K.4
-
26
-
-
29144453489
-
A unifying view of sparse approximate Gaussian process regression
-
QUI ?NONERO CANDELA, J. & RASMUSSEN, C. E. (2005). A unifying view of sparse approximate Gaussian process regression. J. Mach. Learn. Res. 6, 1939-59.
-
(2005)
J. Mach. Learn. Res
, vol.6
, pp. 1939-1959
-
-
Qui Nonero Candela, J.1
Rasmussen, C.E.2
-
28
-
-
35348901208
-
Improved approximation algorithms for large matrices via random projections
-
SARLOS, T. (2006). Improved approximation algorithms for large matrices via random projections. In Proc. 47th Ann. IEEE Symp. Found. Comp. Sci. pp. 143-52.
-
(2006)
Proc. 47th Ann. IEEE Symp. Found. Comp. Sci
, pp. 143-152
-
-
Sarlos, T.1
-
29
-
-
85156215194
-
Transductive and inductive methods for approximate Gaussian process regression
-
SCHWAIGHOFER, A. & TRESP, V. (2002). Transductive and inductive methods for approximate Gaussian process regression. Adv. Neural Info. Proces. Syst. 15, 953-60.
-
(2002)
Adv. Neural Info. Proces. Syst
, vol.15
, pp. 953-960
-
-
Schwaighofer, A.1
Tresp, V.2
-
34
-
-
0027879547
-
On the early history of the singular value decomposition
-
STEWART, G. W. (1993). On the early history of the singular value decomposition. SIAM Rev. 35, 551-66.
-
(1993)
SIAM Rev
, vol.35
, pp. 551-566
-
-
Stewart, G.W.1
-
35
-
-
35349023855
-
Towards a faster implementation of density estimation with logistic Gaussian process priors
-
TOKDAR, S. T. (2007). Towards a faster implementation of density estimation with logistic Gaussian process priors. J. Comp. Graph. Statist. 16, 633-55.
-
(2007)
J. Comp. Graph. Statist
, vol.16
, pp. 633-655
-
-
Tokdar, S.T.1
-
36
-
-
51049088387
-
Rates of contraction of posterior distributions based on Gaussian process priors
-
VAN DER VAART, A. W. & VAN ZANTEN, J. H. (2008). Rates of contraction of posterior distributions based on Gaussian process priors. Ann. Statist. 36, 1435-63.
-
(2008)
Ann. Statist
, vol.36
, pp. 1435-1463
-
-
Van Der Vaart, A.W.1
Van Zanten, J.H.2
|