-
1
-
-
84863516562
-
-
PhD thesis, School of Computer Science, University of Manchester, Manchester, UK
-
M. A. Álvarez, "Convolved Gaussian process priors for multivariate regression with applications to dynamical systems, " PhD thesis, School of Computer Science, University of Manchester, Manchester, UK, 2011.
-
(2011)
Convolved Gaussian Process Priors for Multivariate Regression with Applications to Dynamical Systems
-
-
Álvarez, M.A.1
-
2
-
-
84858759793
-
Sparse convolved Gaussian processes for multi-output regression
-
(D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, eds.) Cambridge, MA: MIT Press
-
M. A. Álvarez and N. D. Lawrence, "Sparse convolved Gaussian processes for multi-output regression, " in Advances in Neural Information Processing Systems (NIPS), vol. 21, (D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, eds.), pp. 57-64, Cambridge, MA: MIT Press, 2009.
-
(2009)
Advances in Neural Information Processing Systems (NIPS)
, vol.21
, pp. 57-64
-
-
Álvarez, M.A.1
Lawrence, N.D.2
-
3
-
-
80053151379
-
Latent force models
-
(D. van Dyk and M. Welling, eds.) Clearwater Beach, Florida, 16-18 April JMLR W&CP 5
-
M. A. Álvarez, D. Luengo, and N. D. Lawrence, "Latent Force Models, " in Proceedings of the International Conference on Artificial Intelligence and Statistics, (D. van Dyk and M. Welling, eds.), pp. 9-16, Clearwater Beach, Florida, 16-18 April 2009. JMLR W&CP 5.
-
(2009)
Proceedings of the International Conference on Artificial Intelligence and Statistics
, pp. 9-16
-
-
Álvarez, M.A.1
Luengo, D.2
Lawrence, N.D.3
-
4
-
-
55149088329
-
Convex multi-task feature learning
-
A. Argyriou, T. Evgeniou, and M. Pontil, "Convex multi-task feature learning, " Machine Learning, vol. 73, no. 3, pp. 243-272, 2008.
-
(2008)
Machine Learning
, vol.73
, Issue.3
, pp. 243-272
-
-
Argyriou, A.1
Evgeniou, T.2
Pontil, M.3
-
5
-
-
56049122238
-
An algorithm for transfer learning in a heterogeneous environment
-
A. Argyriou, A. Maurer, and M. Pontil, "An algorithm for transfer learning in a heterogeneous environment, " in Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databse-Part I (ECML/PKDD), pp. 71-85, 2008.
-
Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databse-Part i (ECML/PKDD)
, vol.2008
, pp. 71-85
-
-
Argyriou, A.1
Maurer, A.2
Pontil, M.3
-
7
-
-
84863525439
-
-
Technical Report, Massachusetts Institute of Technology, MIT-CSAIL-TR-2011-004, CBCL-296
-
L. Baldassarre, L. Rosasco, A. Barla, and A. Verri, "Multi-output learning via spectral filtering, " Technical Report, Massachusetts Institute of Technology, MIT-CSAIL-TR-2011-004, CBCL-296, 2011.
-
(2011)
Multi-output Learning Via Spectral Filtering
-
-
Baldassarre, L.1
Rosasco, L.2
Barla, A.3
Verri, A.4
-
8
-
-
0030436141
-
Blackbox kriging: Spatial prediction without specifying variogram models
-
R. P. Barry and J. M. Ver Hoef, "Blackbox kriging: spatial prediction without specifying variogram models, " Journal of Agricultural, Biological and Environmental Statistics, vol. 1, no. 3, pp. 297-322, 1996.
-
(1996)
Journal of Agricultural, Biological and Environmental Statistics
, vol.1
, Issue.3
, pp. 297-322
-
-
Barry, R.P.1
Ver Hoef, J.M.2
-
9
-
-
70349759974
-
Predicting vehicle crashworthiness: Validation of computer models for functional and hierarchical data
-
M. J. Bayarri, J. O. Berger, M. C. Kennedy, A. Kottas, R. Paulo, J. Sacks, J. A. Cafeo, C.-H. Lin, and J. Tu, "Predicting vehicle crashworthiness: Validation of computer models for functional and hierarchical data, " Journal of the American Statistical Association, vol. 104, no. 487, pp. 929-943, 2009.
-
(2009)
Journal of the American Statistical Association
, vol.104
, Issue.487
, pp. 929-943
-
-
Bayarri, M.J.1
Berger, J.O.2
Kennedy, M.C.3
Kottas, A.4
Paulo, R.5
Sacks, J.6
Cafeo, J.A.7
Lin, C.-H.8
Tu, J.9
-
11
-
-
85161999621
-
Gaussian process preference elicitation
-
Cambridge, MA: MIT Press
-
E. Bonilla, S. Guo, and S. Sanner, "Gaussian process preference elicitation, " in Advances in Neural Information Processing Systems (NIPS), vol. 24, pp. 262-270, Cambridge, MA: MIT Press, 2011.
-
(2011)
Advances in Neural Information Processing Systems (NIPS)
, vol.24
, pp. 262-270
-
-
Bonilla, E.1
Guo, S.2
Sanner, S.3
-
12
-
-
85161977902
-
Multi-task Gaussian process prediction
-
(J. C. Platt, D. Koller, Y. Singer, and S. Roweis, eds.), Cambridge, MA: MIT Press
-
E. V. Bonilla, K. M. Chai, and C. K. I. Williams, "Multi-task Gaussian process prediction, " in Advances in Neural Information Processing Systems (NIPS)vol. 20, (J. C. Platt, D. Koller, Y. Singer, and S. Roweis, eds.), Cambridge, MA: MIT Press, 2008.
-
(2008)
Advances in Neural Information Processing Systems (NIPS)
, vol.20
-
-
Bonilla, E.V.1
Chai, K.M.2
Williams, C.K.I.3
-
13
-
-
58349090162
-
-
PhD thesis, Victoria University of Wellington, Wellington, New Zealand
-
P. Boyle, "Gaussian processes for regression and optimisation, " PhD thesis, Victoria University of Wellington, Wellington, New Zealand, 2007.
-
(2007)
Gaussian Processes for Regression and Optimisation
-
-
Boyle, P.1
-
14
-
-
84898973907
-
Dependent gaussian processes
-
(L. Saul, Y. Weiss, and L. Bouttou, eds.) Cambridge, MA: MIT Press
-
P. Boyle and M. Frean, "Dependent Gaussian processes, " in Advances in Neural Information Processing Systems (NIPS), vol. 17, (L. Saul, Y. Weiss, and L. Bouttou, eds.), pp. 217-224, Cambridge, MA: MIT Press, 2005.
-
(2005)
Advances in Neural Information Processing Systems (NIPS)
, vol.17
, pp. 217-224
-
-
Boyle, P.1
Frean, M.2
-
15
-
-
79959205293
-
Multiple output Gaussian process regression
-
School of Mathematical and Computing Sciences, Victoria University, New Zealand
-
P. Boyle and M. Frean, "Multiple output Gaussian process regression, " Technical Report CS-TR-05/2, School of Mathematical and Computing Sciences, Victoria University, New Zealand, 2005.
-
(2005)
Technical Report CS-TR-05/2
-
-
Boyle, P.1
Frean, M.2
-
16
-
-
38349102465
-
A dynamic process convolution approach to modeling ambient particulate matter concentrations
-
C. A. Calder, "A dynamic process convolution approach to modeling ambient particulate matter concentrations, " Environmetrics, vol. 19, pp. 39-48, 2008.
-
(2008)
Environmetrics
, vol.19
, pp. 39-48
-
-
Calder, C.A.1
-
18
-
-
48849098893
-
Universal kernels for multi-task learning
-
A. Caponnetto, C. Micchelli, M. Pontil, and Y. Ying, "Universal kernels for multi-task learning, " Journal of Machine Learning Research, vol. 9, pp. 1615-1646, 2008.
-
(2008)
Journal of Machine Learning Research
, vol.9
, pp. 1615-1646
-
-
Caponnetto, A.1
Micchelli, C.2
Pontil, M.3
Ying, Y.4
-
19
-
-
48849086653
-
Vector valued reproducing kernel Hilbert spaces of integrable functions and Mercer theorem
-
C. Carmeli, E. De Vito, and A. Toigo, "Vector valued reproducing kernel Hilbert spaces of integrable functions and Mercer theorem, " Analysis and Applications (Singapore), vol. 4, no. 4, pp. 377-408, 2006.
-
(2006)
Analysis and Applications (Singapore)
, vol.4
, Issue.4
, pp. 377-408
-
-
Carmeli, C.1
De Vito, E.2
Toigo, A.3
-
20
-
-
0031189914
-
Multitask learning
-
R. Caruana, "Multitask learning, " Machine Learning, vol. 28, pp. 41-75, 1997. (Pubitemid 127507169)
-
(1997)
Machine Learning
, vol.28
, Issue.1
, pp. 41-75
-
-
Caruana, R.1
-
21
-
-
78349302239
-
Generalization errors and learning curves for regression with multi-task Gaussian processes
-
(Y. Bengio, D. Schuurmans, J. Laferty, C. Williams, and A. Culotta, eds.) Cambridge, MA: MIT Press
-
K. M. Chai, "Generalization errors and learning curves for regression with multi-task Gaussian processes, " in Advances in Neural Information Processing Systems (NIPS), vol. 22, (Y. Bengio, D. Schuurmans, J. Laferty, C. Williams, and A. Culotta, eds.), pp. 279-287, Cambridge, MA: MIT Press, 2010.
-
(2010)
Advances in Neural Information Processing Systems (NIPS)
, vol.22
, pp. 279-287
-
-
Chai, K.M.1
-
22
-
-
79960122862
-
Multitask Gaussian process learning of robot inverse dynamics
-
(D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, eds.) Cambridge, MA: MIT Press
-
K. M. A. Chai, C. K. I. Williams, S. Klanke, and S. Vijayakumar, "Multitask Gaussian process learning of robot inverse dynamics, " in Advances in Neural Information Processing Systems (NIPS), (D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, eds.), pp. 265-272, Cambridge, MA: MIT Press, 2009.
-
(2009)
Advances in Neural Information Processing Systems (NIPS)
, pp. 265-272
-
-
Chai, K.M.A.1
Williams, C.K.I.2
Klanke, S.3
Vijayakumar, S.4
-
23
-
-
70350733506
-
Bayesian emulation of complex multi-output and dynamic computer models
-
S. Conti and A. O'Hagan, "Bayesian emulation of complex multi-output and dynamic computer models, " Journal of Statistical Planning and Inference, vol. 140, no. 3, pp. 640-651, 2010.
-
(2010)
Journal of Statistical Planning and Inference
, vol.140
, Issue.3
, pp. 640-651
-
-
Conti, S.1
O'Hagan, A.2
-
25
-
-
0036071370
-
On the mathematical foundations of learning
-
(electronic)
-
F. Cucker and S. Smale, "On the mathematical foundations of learning, " Bulletin of the American Mathematical Society (N.S.), vol. 39, no. 1, pp. 1-49, (electronic) 2002.
-
(2002)
Bulletin of the American Mathematical Society (N.S.)
, vol.39
, Issue.1
, pp. 1-49
-
-
Cucker, F.1
Smale, S.2
-
26
-
-
23244462944
-
Some properties of regularized kernel methods
-
E. De Vito, L. Rosasco, A. Caponnetto, M. Piana, and A. Verri, "Some properties of regularized kernel methods, " Journal of Machine Learning Research, vol. 5, pp. 1363-1390, 2004.
-
(2004)
Journal of Machine Learning Research
, vol.5
, pp. 1363-1390
-
-
De Vito, E.1
Rosasco, L.2
Caponnetto, A.3
Piana, M.4
Verri, A.5
-
27
-
-
21844456299
-
Learning multiple tasks with kernel methods
-
T. Evgeniou, C. A. Micchelli, and M. Pontil, "Learning multiple tasks with kernel methods, " Journal of Machine Learning Research, vol. 6, pp. 615-637, 2005.
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 615-637
-
-
Evgeniou, T.1
Micchelli, C.A.2
Pontil, M.3
-
28
-
-
21844456299
-
Learning multiple tasks with kernel methods
-
T. Evgeniou, C. A. Micchelli, and M. Pontil, "Learning multiple tasks with kernel methods, " Journal of Machine Learning Research, vol. 6, pp. 615-637, 2005.
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 615-637
-
-
Evgeniou, T.1
Micchelli, C.A.2
Pontil, M.3
-
29
-
-
80052803648
-
Probabilistic uncertainty analysis of an FRF of a structure using a Gaussian process emulator
-
T. E. Fricker, J. E. Oakley, N. D. Sims, and K. Worden, "Probabilistic uncertainty analysis of an FRF of a structure using a Gaussian process emulator, " Mechanical Systems and Signal Processing, vol. 25, no. 8, pp. 2962-2975, 2011.
-
(2011)
Mechanical Systems and Signal Processing
, vol.25
, Issue.8
, pp. 2962-2975
-
-
Fricker, T.E.1
Oakley, J.E.2
Sims, N.D.3
Worden, K.4
-
30
-
-
84993812365
-
Interpolation of nonstationary air pollution processes: A spatial spectral approach
-
M. Fuentes, "Interpolation of nonstationary air pollution processes: A spatial spectral approach, " Statistical Modelling, vol. 2, pp. 281-298, 2002.
-
(2002)
Statistical Modelling
, vol.2
, pp. 281-298
-
-
Fuentes, M.1
-
31
-
-
0042401905
-
Spectral methods for nonstationary spatial processes
-
DOI 10.1093/biomet/89.1.197
-
M. Fuentes, "Spectral methods for nonstationary spatial processes, " Biometrika, vol. 89, no. 1, pp. 197-210, 2002. (Pubitemid 41312011)
-
(2002)
Biometrika
, vol.89
, Issue.1
, pp. 197-210
-
-
Fuentes, M.1
-
33
-
-
49549105346
-
Gaussian process modelling of latent chemical species: Applications to inferring transcription factor activities
-
P. Gao, A. Honkela, M. Rattray, and N. D. Lawrence, "Gaussian process modelling of latent chemical species: Applications to inferring transcription factor activities, " Bioinformatics, vol. 24, pp. i70-i75, 2008.
-
(2008)
Bioinformatics
, vol.24
-
-
Gao, P.1
Honkela, A.2
Rattray, M.3
Lawrence, N.D.4
-
34
-
-
13444251351
-
Nonstationary multivariate process modeling through spatially varying coregionalization
-
A. E. Gelfand, A. M. Schmidt, S. Banerjee, and C. Sirmans, "Nonstationary multivariate process modeling through spatially varying coregionalization, " TEST, vol. 13, no. 2, pp. 263-312, 2004. (Pubitemid 40217244)
-
(2004)
Test
, vol.13
, Issue.2
, pp. 263-312
-
-
Gelfand, A.E.1
Schmidt, A.M.2
Banerjee, S.3
Sirmans, C.F.4
Fuentes, M.5
Higdon, D.6
Sanso, B.7
-
35
-
-
0024991997
-
Networks and the best approximation property
-
DOI 10.1007/BF00195855
-
F. Girosi and T. Poggio, "Networks and the best approximation property, " Biological Cybernetics, vol. 63, pp. 169-176, 1989. (Pubitemid 20290535)
-
(1990)
Biological Cybernetics
, vol.63
, Issue.3
, pp. 169-176
-
-
Girosi, F.1
Poggio, T.2
-
36
-
-
0035439188
-
Analogies and correspondences between variograms and covariance functions
-
DOI 10.1239/aap/1005091356
-
T. Gneiting, Z. Sasvári, and M. Schlather, "Analogies and correspondences between variograms and covariance functions, " Advances in Applied Probability, vol. 33, no. 3, pp. 617-630, 2001. (Pubitemid 33038952)
-
(2001)
Advances in Applied Probability
, vol.33
, Issue.3
, pp. 617-630
-
-
Gneiting, T.1
Sasvari, Z.2
Schlather, M.3
-
38
-
-
0026465454
-
Linear coregionalization model: Tools for estimation and choice of cross-variogram matrix
-
M. Goulard and M. Voltz, "Linear coregionalization model: Tools for estimation and choice of cross-variogram matrix, " Mathematical Geology, vol. 24, no. 3, pp. 269-286, 1992.
-
(1992)
Mathematical Geology
, vol.24
, Issue.3
, pp. 269-286
-
-
Goulard, M.1
Voltz, M.2
-
39
-
-
0344789103
-
Coregionalization by linear combination of nonorthogonal components
-
DOI 10.1023/A:1015078911063
-
J. A. V. Guzmán, A. Warrick, and D. E. Myers, " Coregionalization by linear combination of nonorthogonal components, " Mathematical Geology, vol. 34, no. 4, pp. 405-419, 2002. (Pubitemid 41444756)
-
(2002)
Mathematical Geology
, vol.34
, Issue.4
, pp. 405-419
-
-
Vargas-Guzman, J.A.1
Warrick, A.W.2
Myers, D.E.3
-
41
-
-
0028197723
-
Universal cokriging under intrinsic coregionalization
-
J. D. Helterbrand and N. Cressie, "Universal cokriging under intrinsic coregionalization, " Mathematical Geology, vol. 26, no. 2, pp. 205-226, 1994. (Pubitemid 24427109)
-
(1994)
Mathematical Geology
, vol.26
, Issue.2
, pp. 205-226
-
-
Helterbrand, J.D.1
Cressie, N.2
-
42
-
-
49549114864
-
Computer model calibration using high dimensional output
-
D. Higdon, J. Gattiker, B. Williams, and M. Rightley, "Computer model calibration using high dimensional output, " Journal of the American Statistical Association, vol. 103, no. 482, pp. 570-583, 2008.
-
(2008)
Journal of the American Statistical Association
, vol.103
, Issue.482
, pp. 570-583
-
-
Higdon, D.1
Gattiker, J.2
Williams, B.3
Rightley, M.4
-
43
-
-
0032422974
-
A process-convolution approach to modeling temperatures in the North Atlantic Ocean
-
D. M. Higdon, "A process-convolution approach to modeling temperatures in the North Atlantic Ocean, " Journal of Ecological and Environmental Statistics, vol. 5, pp. 173-190, 1998.
-
(1998)
Journal of Ecological and Environmental Statistics
, vol.5
, pp. 173-190
-
-
Higdon, D.M.1
-
44
-
-
2942619617
-
Space and space-time modelling using process convolutions
-
(C. Anderson, V. Barnett, P. Chatwin, and A. El-Shaarawi, eds.) Springer-Verlag
-
D. M. Higdon, "Space and space-time modelling using process convolutions, " in Quantitative methods for current environmental issues, (C. Anderson, V. Barnett, P. Chatwin, and A. El-Shaarawi, eds.), pp. 37-56, Springer-Verlag, 2002.
-
(2002)
Quantitative Methods for Current Environmental Issues
, pp. 37-56
-
-
Higdon, D.M.1
-
45
-
-
0000439277
-
Non-stationary spatial modeling
-
(J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, eds.) Oxford University Press
-
D. M. Higdon, J. Swall, and J. Kern, "Non-stationary spatial modeling, " in Bayesian Statistics 6, (J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, eds.), pp. 761-768, Oxford University Press, 1998.
-
(1998)
Bayesian Statistics
, vol.6
, pp. 761-768
-
-
Higdon, D.M.1
Swall, J.2
Kern, J.3
-
47
-
-
84858783652
-
Clustered multi-task learning: A convex formulation
-
Curran Associates, Inc
-
L. Jacob, F. Bach, and J. Vert, "Clustered multi-task learning: A convex formulation, " in Advances in Neural Information Processing Systems (NIPS), Curran Associates, Inc, 2008.
-
(2008)
Advances in Neural Information Processing Systems (NIPS)
-
-
Jacob, L.1
Bach, F.2
Vert, J.3
-
48
-
-
84858783652
-
Clustered multi-task learning: A convex formulation
-
L. Jacob, F. Bach, and J.-P. Vert, "Clustered multi-task learning: A convex formulation, " in Advances in Neural Information Processing Systems (NIPS) 21, pp. 745-752, 2008.
-
(2008)
Advances in Neural Information Processing Systems (NIPS)
, vol.21
, pp. 745-752
-
-
Jacob, L.1
Bach, F.2
Vert, J.-P.3
-
50
-
-
84899033524
-
Maximal margin labeling for multi-topic text categorization
-
(L. Saul, Y. Weiss, and L. Bouttou, eds.) Cambridge, MA: MIT Press
-
H. Kazawa, T. Izumitani, H. Taira, and E. Maeda, "Maximal margin labeling for multi-topic text categorization, " in Advances in Neural Information Processing Systems (NIPS), vol. 17, (L. Saul, Y. Weiss, and L. Bouttou, eds.), pp. 649-656, Cambridge, MA: MIT Press, 2005.
-
(2005)
Advances in Neural Information Processing Systems (NIPS)
, vol.17
, pp. 649-656
-
-
Kazawa, H.1
Izumitani, T.2
Taira, H.3
Maeda, E.4
-
51
-
-
0000406385
-
A correspondence between Bayesian estimation of stochastic processes and smoothing by splines
-
G. Kimeldorf and G. Wahba, "A correspondence between Bayesian estimation of stochastic processes and smoothing by splines, " Annals of Mathematical Statistics, vol. 41, pp. 495-502, 1970.
-
(1970)
Annals of Mathematical Statistics
, vol.41
, pp. 495-502
-
-
Kimeldorf, G.1
Wahba, G.2
-
52
-
-
77955810643
-
-
Cambridge, MA: MIT Press
-
D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, eds., Advances in Neural Information Processing Systems (NIPS). vol. 21, Cambridge, MA: MIT Press, 2009.
-
(2009)
Advances in Neural Information Processing Systems (NIPS)
, vol.21
-
-
Koller, D.1
Schuurmans, D.2
Bengio, Y.3
Bottou, L.4
-
53
-
-
0031423171
-
Generalized cross-covariances and their estimation
-
H. Künsch, A. Papritz, and F. Bassi, "Generalized cross-covariances and their estimation, " Mathematical Geology, vol. 29, no. 6, pp. 779-799, 1997. (Pubitemid 28096724)
-
(1997)
Mathematical Geology
, vol.29
, Issue.6
, pp. 779-799
-
-
Kunsch, H.R.1
Papritz, A.2
Bassi, F.3
-
54
-
-
0041360093
-
Fitting a linear model of coregionalization for soil properties using simulated annealing
-
DOI 10.1016/S0016-7061(03)00065-X
-
R. M. Lark and A. Papritz, "Fitting a linear model of coregionalization for soil properties using simulated annealing, " Geoderma, vol. 115, pp. 245-260, 2003. (Pubitemid 37060370)
-
(2003)
Geoderma
, vol.115
, Issue.3-4
, pp. 245-260
-
-
Lark, R.M.1
Papritz, A.2
-
55
-
-
14344249890
-
Learning to learn with the informative vector machine
-
Proceedings, Twenty-First International Conference on Machine Learning, ICML 2004
-
N. D. Lawrence and J. C. Platt, "Learning to learn with the informative vector machine, " in Proceedings of the International Conference on Machine Learning (ICML 2004), pp. 512-519, 2004. (Pubitemid 40290848)
-
(2004)
Proceedings, Twenty-First International Conference on Machine Learning, ICML 2004
, pp. 512-519
-
-
Lawrence, N.D.1
Platt, J.C.2
-
56
-
-
84864060452
-
Modelling transcriptional regulation using Gaussian Processes
-
(B. Schölkopf, J. C. Platt, and T. Hofmann, eds.) Cambridge, MA: MIT Press
-
N. D. Lawrence, G. Sanguinetti, and M. Rattray, "Modelling transcriptional regulation using Gaussian Processes, " in Advances in Neural Information Processing Systems (NIPS), vol. 19, (B. Schölkopf, J. C. Platt, and T. Hofmann, eds.), pp. 785-792, Cambridge, MA: MIT Press, 2007.
-
(2007)
Advances in Neural Information Processing Systems (NIPS)
, vol.19
, pp. 785-792
-
-
Lawrence, N.D.1
Sanguinetti, G.2
Rattray, M.3
-
57
-
-
80053225881
-
Fast sparse Gaussian process methods: The informative vector machine
-
(S. Becker, S. Thrun, and K. Obermayer, eds.) Cambridge, MA: MIT Press
-
N. D. Lawrence, M. Seeger, and R. Herbrich, "Fast sparse Gaussian process methods: The informative vector machine, " in Advances in Neural Information Processing Systems (NIPS), vol. 15, (S. Becker, S. Thrun, and K. Obermayer, eds.), pp. 625-632, Cambridge, MA: MIT Press, 2003.
-
(2003)
Advances in Neural Information Processing Systems (NIPS)
, vol.15
, pp. 625-632
-
-
Lawrence, N.D.1
Seeger, M.2
Herbrich, R.3
-
58
-
-
68149134506
-
-
Department of Statistical Science, Duke University, Discussion Paper 07-10. (Submitted for publication)
-
F. Liang, K. Mao, M. Liao, S. Mukherjee, and M. West, "Non-parametric Bayesian kernel models, " Department of Statistical Science, Duke University, Discussion Paper 07-10. (Submitted for publication), 2009.
-
(2009)
Non-parametric Bayesian Kernel Models
-
-
Liang, F.1
Mao, K.2
Liao, M.3
Mukherjee, S.4
West, M.5
-
59
-
-
17444417421
-
A density theorem for matrix-valued radial basis functions
-
DOI 10.1007/s11075-004-3641-x
-
S. Lowitzsch, "A density theorem for matrix-valued radial basis functions, " Numerical Algorithms, vol. 39, no. 1, pp. 253-256, 2005. (Pubitemid 40550236)
-
(2005)
Numerical Algorithms
, vol.39
, Issue.1-3
, pp. 253-256
-
-
Lowitzsch, S.1
-
61
-
-
34248573628
-
Multivariate spatial modeling for geostatistical data using convolved covariance functions
-
A. Majumdar and A. E. Gelfand, "Multivariate spatial modeling for geostatistical data using convolved covariance functions, " Mathematical Geology, vol. 39, no. 2, pp. 225-244, 2007.
-
(2007)
Mathematical Geology
, vol.39
, Issue.2
, pp. 225-244
-
-
Majumdar, A.1
Gelfand, A.E.2
-
62
-
-
0015764255
-
The intrinsic random functions and their applications
-
G. Matheron, "The intrinsic random functions and their applications, " Advances in Applied Probability, vol. 5, no. 3, pp. 439-468, 1973.
-
(1973)
Advances in Applied Probability
, vol.5
, Issue.3
, pp. 439-468
-
-
Matheron, G.1
-
63
-
-
44849090348
-
Calibration and uncertainty analysis for computer simulations with multivariate output
-
J. McFarland, S. Mahadevan, V. Romero, and L. Swiler, "Calibration and Uncertainty Analysis for Computer Simulations with Multivariate Output, " American Institute of Aeronautics and Astronautics Journal, vol. 46, no. 5, pp. 1253-1265, 2008.
-
(2008)
American Institute of Aeronautics and Astronautics Journal
, vol.46
, Issue.5
, pp. 1253-1265
-
-
McFarland, J.1
Mahadevan, S.2
Romero, V.3
Swiler, L.4
-
64
-
-
14544299611
-
On learning vector-valued functions
-
DOI 10.1162/0899766052530802
-
C. Micchelli and M. Pontil, "On learning vector-valued functions, " Neural Computation, vol. 17, pp. 177-204, 2005. (Pubitemid 40305887)
-
(2005)
Neural Computation
, vol.17
, Issue.1
, pp. 177-204
-
-
Micchelli, C.A.1
Pontil, M.2
-
66
-
-
84863503174
-
Learning how to learn is learning with point sets
-
T. P. Minka and R. W. Picard, "Learning how to learn is learning with point sets, " Revised version 1999 available at http://research. microsoft.com/enus/ um/people/minka/papers/point-sets.html, 1999.
-
(1999)
Revised Version
, vol.1999
-
-
Minka, T.P.1
Picard, R.W.2
-
67
-
-
33646015688
-
Transformation of Gaussian process priors
-
(J. Winkler, M. Niranjan, and N. Lawrence, eds.) LNAI 3635, Springer-Verlag
-
R. Murray-Smith and B. A. Pearlmutter, "Transformation of Gaussian process priors, " in Deterministic and Statistical Methods in Machine Learning, (J. Winkler, M. Niranjan, and N. Lawrence, eds.), pp. 110-123, LNAI 3635, Springer-Verlag, 2005.
-
(2005)
Deterministic and Statistical Methods in Machine Learning
, pp. 110-123
-
-
Murray-Smith, R.1
Pearlmutter, B.A.2
-
68
-
-
84968510026
-
Generalized Hermite interpolation via matrix-valued conditionally positive definite functions
-
F. Narcowich and J. Ward, "Generalized Hermite interpolation via matrix-valued conditionally positive definite functions, " Mathematics of Computation, vol. 63, no. 208, pp. 661-687, 1994.
-
(1994)
Mathematics of Computation
, vol.63
, Issue.208
, pp. 661-687
-
-
Narcowich, F.1
Ward, J.2
-
69
-
-
77953322499
-
Joint covariate selection and joint subspace selection for multiple classification problems
-
G. Obozinski, B. Taskar, and M. Jordan, "Joint covariate selection and joint subspace selection for multiple classification problems, " Statistics and Computing, vol. 20, no. 2, pp. 231-252, 2010.
-
(2010)
Statistics and Computing
, vol.20
, Issue.2
, pp. 231-252
-
-
Obozinski, G.1
Taskar, B.2
Jordan, M.3
-
70
-
-
33745699573
-
Bayesian analysis of computer code outputs: A tutorial
-
A. O'Hagan, "Bayesian analysis of computer code outputs: A tutorial, " Reliability Engineering and System Safety, vol. 91, pp. 1290-1300, 2006.
-
(2006)
Reliability Engineering and System Safety
, vol.91
, pp. 1290-1300
-
-
O'Hagan, A.1
-
71
-
-
49149117453
-
-
Technical Report, Department of Engineering Science, University of Oxford
-
M. A. Osborne and S. J. Roberts, "Gaussian processes for prediction, " Technical Report, Department of Engineering Science, University of Oxford, 2007.
-
(2007)
Gaussian Processes for Prediction
-
-
Osborne, M.A.1
Roberts, S.J.2
-
72
-
-
51249108949
-
Towards real-time information processing of sensor network data using computationally efficient multi-output Gaussian processes
-
M. A. Osborne, A. Rogers, S. D. Ramchurn, S. J. Roberts, and N. R. Jennings, "Towards real-time information processing of sensor network data using computationally efficient multi-output Gaussian processes, " in Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN 2008), 2008.
-
(2008)
Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN 2008)
-
-
Osborne, M.A.1
Rogers, A.2
Ramchurn, S.D.3
Roberts, S.J.4
Jennings, N.R.5
-
73
-
-
84899028582
-
Nonstationary covariance functions for Gaussian process regression
-
(S. Thrun, L. Saul, and B. Schölkopf, eds.), Cambridge, MA: MIT Press
-
C. J. Paciorek and M. J. Schervish, "Nonstationary covariance functions for Gaussian process regression, " in Advances in Neural Information Processing Systems (NIPS) 16, (S. Thrun, L. Saul, and B. Schölkopf, eds.), Cambridge, MA: MIT Press, 2004.
-
(2004)
Advances in Neural Information Processing Systems (NIPS)
, vol.16
-
-
Paciorek, C.J.1
Schervish, M.J.2
-
74
-
-
77956031473
-
A survey on transfer learning
-
October
-
S. J. Pan and Q. Yang, "A survey on transfer learning, " IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 10, pp. 1345-1359, October 2010.
-
(2010)
IEEE Transactions on Knowledge and Data Engineering
, vol.22
, Issue.10
, pp. 1345-1359
-
-
Pan, S.J.1
Yang, Q.2
-
75
-
-
0027807842
-
On the pseudo cross-variogram
-
A. Papritz, H. Künsch, and R. Webster, "On the Pseudo cross-variogram, " Mathematical Geology, vol. 25, no. 8, pp. 1015-1026, 1993. (Pubitemid 24422457)
-
(1993)
Mathematical Geology
, vol.25
, Issue.8
, pp. 1015-1026
-
-
Papritz, A.1
Kunsch, H.R.2
Webster, R.3
-
76
-
-
3042803149
-
Fitting the linear model of coregionalization by generalized least squares
-
B. Pelletier, P. Dutilleul, G. Larocque, and J. W. Fyles, "Fitting the linear model of coregionalization by generalized least squares, " Mathematical Geology, vol. 36, no. 3, pp. 323-343, 2004.
-
(2004)
Mathematical Geology
, vol.36
, Issue.3
, pp. 323-343
-
-
Pelletier, B.1
Dutilleul, P.2
Larocque, G.3
Fyles, J.W.4
-
77
-
-
34547900221
-
Characterizing the function space for bayesian kernel models
-
N. S. Pillai, Q. Wu, F. Liang, S. Mukherjee, and R. L. Wolpert, "Characterizing the function space for Bayesian kernel models, " Journal of Machine Learning Research, vol. 8, pp. 1769-1797, 2007. (Pubitemid 47258008)
-
(2007)
Journal of Machine Learning Research
, vol.8
, pp. 1769-1797
-
-
Pillai, N.S.1
Wu, Q.2
Liang, F.3
Mukherjee, S.4
Wolpert, R.L.5
-
78
-
-
0025490985
-
Networks for approximation and learning
-
T. Poggio and F. Girosi, "Networks for approximation and learning, " Proceedings of the IEEE, vol. 78, no. 9, pp. 1481-1497, 1990.
-
(1990)
Proceedings of the IEEE
, vol.78
, Issue.9
, pp. 1481-1497
-
-
Poggio, T.1
Girosi, F.2
-
79
-
-
55149088117
-
Gaussian process models for computer experiments with qualitative and quantitative factors
-
P. Z. G. Qian, H.Wu, and C. F. J.Wu, "Gaussian process models for computer experiments with qualitative and quantitative factors, " Technometrics, vol. 50, no. 3, pp. 383-396, 2008.
-
(2008)
Technometrics
, vol.50
, Issue.3
, pp. 383-396
-
-
Qian, P.Z.G.1
Wu, H.2
Wu, C.F.J.3
-
80
-
-
29144453489
-
A unifying view of sparse approximate Gaussian process regression
-
J. Quiñonero-Candela and C. E. Rasmussen, "A unifying view of sparse approximate Gaussian process regression, " Journal of Machine Learning Research, vol. 6, pp. 1939-1959, 2005. (Pubitemid 41798128)
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 1939-1959
-
-
Quinonero-Candela, J.1
Rasmussen, C.E.2
-
81
-
-
24144465874
-
Analysis of some methods for Reduced Rank Gaussian Process Regression
-
Switching and Learning in Feedback Systems - European Summer School on Multi-Agent Control
-
J. Quiñonero-Candela and C. E. Rasmussen, "Analysis of some methods for reduced rank Gaussian process regression, " in Lecture Notes in Computer Science, (R. Murray-Smith and R. Shorten, eds.), pp. 98-127, Springer, 2005. (Pubitemid 41228755)
-
(2005)
Lecture Notes in Computer Science
, vol.3355
, pp. 98-127
-
-
Quinonero-Candela, J.1
Rasmussen, C.E.2
-
83
-
-
64249139703
-
Efficient emulators for multivariate deterministic functions
-
J. Rougier, "Efficient emulators for multivariate deterministic functions, " Journal of Computational and Graphical Statistics, vol. 17, no. 4, pp. 827-834, 2008.
-
(2008)
Journal of Computational and Graphical Statistics
, vol.17
, Issue.4
, pp. 827-834
-
-
Rougier, J.1
-
85
-
-
33646519705
-
-
Cambridge, MA: MIT Press
-
L. Saul, Y. Weiss, and L. Bouttou, eds., Advances in Neural Information Processing Systems (NIPS). vol. 17, Cambridge, MA: MIT Press, 2005.
-
(2005)
Advances in Neural Information Processing Systems (NIPS)
, vol.17
-
-
Saul, L.1
Weiss, Y.2
Bouttou, L.3
-
87
-
-
84865131152
-
A generalized representer theorem
-
Computational Learning Theory
-
B. Schšlkopf, R. Herbrich, and A. J. Smola, "A generalized representer theorem, " in Proceedings of the Annual Conference on Computational Learning Theory (COLT), pp. 416-426, 2001. (Pubitemid 33312837)
-
(2001)
Lecture Notes in Computer Science
, Issue.2111
, pp. 416-426
-
-
Scholkopf, B.1
Herbrich, R.2
Smola, A.J.3
-
88
-
-
51649141644
-
Sous-espaces hilbertiens d'espaces vectoriels topologiques et noyaux associés (noyaux reproduisants)
-
L. Schwartz, "Sous-espaces hilbertiens d'espaces vectoriels topologiques et noyaux associés (noyaux reproduisants), " Journal d'Analyse Mathématique, vol. 13, pp. 115-256, 1964.
-
(1964)
Journal d'Analyse Mathématique
, vol.13
, pp. 115-256
-
-
Schwartz, L.1
-
91
-
-
78049323760
-
-
Technical Report, Cornell University, Preprint
-
D. Sheldon, "Graphical multi-task learning, " Technical Report, Cornell University, Preprint, 2008.
-
(2008)
Graphical Multi-task Learning
-
-
Sheldon, D.1
-
92
-
-
24144438211
-
Filtered Gaussian processes for learning with large data-sets
-
Switching and Learning in Feedback Systems - European Summer School on Multi-Agent Control
-
J. Q. Shi, R. Murray-Smith, D. Titterington, and B. Pearlmutter, "Learning with large data sets using filtered Gaussian process priors, " in Proceedings of the Hamilton Summer School on Switching and Learning in Feedback Systems, (R. Murray-Smith and R. Shorten, eds.), pp. 128-139, LNCS 3355, Springer- Verlag, 2005. (Pubitemid 41228756)
-
(2005)
Lecture Notes in Computer Science
, vol.3355
, pp. 128-139
-
-
Shi, J.Q.1
Murray-Smith, R.2
Titterington, D.M.3
Pearlmutter, B.A.4
-
93
-
-
83855165736
-
Bayesian multitask classification with Gaussian process priors
-
G. Skolidis and G. Sanguinetti, "Bayesian multitask classification With Gaussian process priors, " IEEE Transactions on Neural Networks, vol. 22, no. 12, pp. 2011-2021, 2011.
-
(2011)
IEEE Transactions on Neural Networks
, vol.22
, Issue.12
, pp. 2011-2021
-
-
Skolidis, G.1
Sanguinetti, G.2
-
94
-
-
84863516571
-
Learning sparse inverse covariance matrices in the presence of confounders
-
O. Stegle, C. Lippert, J. Mooij, N. Lawrence, and K. Borgwardt, "Learning sparse inverse covariance matrices in the presence of confounders, " in Neural Information Processing Systems, 2011.
-
(2011)
Neural Information Processing Systems
-
-
Stegle, O.1
Lippert, C.2
Mooij, J.3
Lawrence, N.4
Borgwardt, K.5
-
96
-
-
84862602372
-
Semiparametric latent factor models
-
(R. G. Cowell and Z. Ghahramani, eds.) Barbados: Society for Artificial Intelligence and Statistics, 6-8 January
-
Y. W. Teh, M. Seeger, and M. I. Jordan, "Semiparametric latent factor models, " in Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics (AISTATS 10), (R. G. Cowell and Z. Ghahramani, eds.), pp. 333-340, Barbados: Society for Artificial Intelligence and Statistics, 6-8 January 2005.
-
(2005)
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics (AISTATS 10)
, pp. 333-340
-
-
Teh, Y.W.1
Seeger, M.2
Jordan, M.I.3
-
97
-
-
85031124575
-
Is learning the n-thing any easier than learning the first?
-
(D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, eds.) Cambridge, MA: MIT Press
-
S. Thrun, "Is learning the n-thing any easier than learning the first?, " in Advances in Neural Information Processing Systems (NIPS), vol. 08, (D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, eds.), pp. 640-646, Cambridge, MA: MIT Press, 1996.
-
(1996)
Advances in Neural Information Processing Systems (NIPS) 08
, pp. 640-646
-
-
Thrun, S.1
-
99
-
-
83855162680
-
Efficient sampling for Gaussian process inference using control variables
-
(D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, eds.) Cambridge, MA: MIT Press
-
M. Titsias, N. D. Lawrence, and M. Rattray, "Efficient sampling for Gaussian process inference using control variables, " in Advances in Neural Information Processing Systems (NIPS), (D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, eds.), pp. 1681-1688, Cambridge, MA: MIT Press, 2009.
-
(2009)
Advances in Neural Information Processing Systems (NIPS)
, pp. 1681-1688
-
-
Titsias, M.1
Lawrence, N.D.2
Rattray, M.3
-
102
-
-
0032525527
-
Constructing and fitting models for cokriging and multivariable spatial prediction
-
PII S0378375897001626
-
J. M. Ver Hoef and R. P. Barry, "Constructing and fitting models for cokriging and multivariable spatial prediction, " Journal of Statistical Planning and Inference, vol. 69, pp. 275-294, 1998. (Pubitemid 128182034)
-
(1998)
Journal of Statistical Planning and Inference
, vol.69
, Issue.2
, pp. 275-294
-
-
Ver Hoef, J.M.1
Barry, R.P.2
-
103
-
-
3042679820
-
Flexible spatial models for kriging and cokriging using moving averages and the fast Fourier Transform (FFT)
-
DOI 10.1198/1061860043498
-
J. M. Ver Hoef, N. Cressie, and R. P. Barry, "Flexible spatial models for kriging and cokriging using moving averages and the Fast Fourier Transform (FFT), " Journal of Computational and Graphical Statistics, vol. 13, no. 2, pp. 265-282, 2004. (Pubitemid 38845885)
-
(2004)
Journal of Computational and Graphical Statistics
, vol.13
, Issue.2
, pp. 265-282
-
-
Ver Hoef, J.M.1
Cressie, N.2
Barry, R.P.3
-
106
-
-
37549055132
-
Gaussian process dynamical models for human motion
-
J. M. Wang, D. J. Fleet, and A. Hertzmann, "Gaussian process dynamical models for human motion, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 2, pp. 283-298, 2008.
-
(2008)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.30
, Issue.2
, pp. 283-298
-
-
Wang, J.M.1
Fleet, D.J.2
Hertzmann, A.3
-
107
-
-
84993723115
-
A kernel-based spectral model for non-Gaussian spatio-temporal processes
-
C. K. Wikle, "A kernel-based spectral model for non-Gaussian spatio-temporal processes, " Statistical Modelling, vol. 2, pp. 299-314, 2002.
-
(2002)
Statistical Modelling
, vol.2
, pp. 299-314
-
-
Wikle, C.K.1
-
108
-
-
0041985115
-
Hierarchical Bayesian models for predicting the spread of ecological processes
-
C. K. Wikle, "Hierarchical Bayesian models for predicting the spread of ecological processes, " Ecology, vol. 84, no. 6, pp. 1382-1394, 2003. (Pubitemid 37435724)
-
(2003)
Ecology
, vol.84
, Issue.6
, pp. 1382-1394
-
-
Wikle, C.K.1
-
109
-
-
0032409329
-
Hierarchical Bayesian space-time models
-
DOI 10.1023/A:1009662704779
-
C. K. Wikle, L. M. Berliner, and N. Cressie, "Hierarchical Bayesian space-time models, " Environmental and Ecological Statistics, vol. 5, pp. 117-154, 1998. (Pubitemid 29033779)
-
(1998)
Environmental and Ecological Statistics
, vol.5
, Issue.2
, pp. 117-154
-
-
Wikle, C.K.1
Berliner, L.M.2
Cressie, N.3
-
110
-
-
0032289422
-
Bayesian classification with gaussian processes
-
C. K. Williams and D. Barber, "Bayesian Classification with Gaussian processes, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 12, pp. 1342-1351, 1998. (Pubitemid 128741378)
-
(1998)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.20
, Issue.12
, pp. 1342-1351
-
-
Williams, C.K.I.1
Barber, D.2
-
111
-
-
0032576668
-
Vegetation-climate feedbacks in a greenhouse world
-
I.Woodward, M. R. Lomas, and R. A. Betts, "Vegetation-climate feedbacks in a greenhouse world, " Philosophical Transactions: Biological Sciences, vol. 353, no. 1365, pp. 29-39, 1998.
-
(1998)
Philosophical Transactions: Biological Sciences
, vol.353
, Issue.1365
, pp. 29-39
-
-
Woodward, I.1
Lomas, M.R.2
Betts, R.A.3
-
112
-
-
33846487387
-
Multi-task learning for classification with Dirichlet process priors
-
Y. Xue, X. Liao, and L. Carin, "Multi-task learning for classification with Dirichlet process priors, " Journal of Machine Learning Research, vol. 8, pp. 35-63, 2007. (Pubitemid 46155123)
-
(2007)
Journal of Machine Learning Research
, vol.8
, pp. 35-63
-
-
Ya, X.1
Xuejun, L.2
Carin, L.3
Krishnapuram, B.4
-
113
-
-
31844442664
-
Learning Gaussian processes from multiple tasks
-
K. Yu, V. Tresp, and A. Schwaighofer, "Learning Gaussian processes from multiple tasks, " in Proceedings of the International Conference on Machine Learning (ICML 2005), pp. 1012-1019, 2005.
-
(2005)
Proceedings of the International Conference on Machine Learning (ICML 2005)
, pp. 1012-1019
-
-
Yu, K.1
Tresp, V.2
Schwaighofer, A.3
-
114
-
-
33947110315
-
Maximum-likelihood estimation for multivariate spatial linear coregionalization models
-
DOI 10.1002/env.807
-
H. Zhang, "Maximum-likelihood estimation for multivariate spatial linear coregionalization models, " Environmetrics, vol. 18, pp. 125-139, 2007. (Pubitemid 46395831)
-
(2007)
Environmetrics
, vol.18
, Issue.2
, pp. 125-139
-
-
Zhang, H.1
|