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Recent work shows that inference for Gaussian processes can be performed efficiently using iterative methods that rely only on matrix-vector multiplications (MVMs).
An iteration method for the solution of the eigenvalue problem of linear differential and integral operators
Lanczos, C. (1950) · 1950
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A unifying view of sparse approximate gaussian process regression
Quiñonero-Candela, J. and Rasmussen, C. E. (2005) · 1959
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Computational variants of the lanczos method for the eigenproblem
Paige, C. C. (1972) · 1972
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Cubic convolution interpolation for digital image processing
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An introduction to the conjugate gradient method without the agonizing pain
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Low-rank matrix approximation using the lanczos bidiagonalization process with applications
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Infinite mixtures of gaussian process experts
Rasmussen, C. E. and Ghahramani, Z. (2002) · 2002
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Hierarchical gaussian process mixtures for regression
Shi, J. Q., Murray-Smith, R., and Titterington, D. (2005) · 2005
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Gaussian processes for machine learning
Rasmussen, C. E. and Williams, C. K. (2006) · 2006
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Sparse Gaussian processes using pseudo-inputs
Snelson, E. and Ghahramani, Z. (2006) · 2006
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An estimator for the diagonal of a matrix
Bekas, C., Kokiopoulou, E., and Saad, Y. (2007) · 2007
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Multi-task Gaussian process prediction
Bonilla, E. V., Chai, K. M., and Williams, C. (2008) · 2008
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Fast gaussian process methods for point process intensity estimation
Cunningham, J. P., Shenoy, K. V., and Sahani, M. (2008) · 2008
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Bayesian experimental design of magnetic resonance imaging sequences
Nickisch, H., Pohmann, R., Schölkopf, B., and Seeger, M. (2009) · 2009
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Variational learning of inducing variables in sparse gaussian processes
Titsias, M. K. (2009) · 2009
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Computationally efficient convolved multiple output Gaussian processes
Álvarez, M. A. and Lawrence, N. D. (2011) · 2011
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Covariance kernels for fast automatic pattern discovery and extrapolation with gaussian processes
Wilson, A. G. (2014) · 2014
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Multitask gaussian processes for multivariate physiological time-series analysis
Dürichen, R., Pimentel, M. A., Clifton, L., Schweikard, A., and Clifton, D. A. (2015) · 2015
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Psychophysical detection testing with bayesian active learning
Gardner, J. R., Song, X., Weinberger, K. Q., Barbour, D. L., and Cunningham, J. P. (2015) · 2015
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Fast nonparametric clustering of structured time-series
Hensman, J., Rattray, M., and Lawrence, N. D. (2015) · 2015
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A framework for individualizing predictions of disease trajectories by exploiting multi-resolution structure
Schulam, P. and Saria, S. (2015) · 2015
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Durrande, N., Ginsbourger, D., and Roustant, O. (2011) · 2011
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Multiple kernel learning algorithms
Gönen, M. and Alpaydın, E. (2011) · 2011
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Matrix computations
Golub, G. H. and Van Loan, C. F. (2012) · 2012
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Scalable inference for structured Gaussian process models
Saatçi, Y. (2012) · 2012
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Improving stochastic estimates with inference methods: Calculating matrix diagonals
Selig, M., Oppermann, N., and Enßlin, T. A. (2012) · 2012
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Practical bayesian optimization of machine learning algorithms
Snoek, J., Larochelle, H., and Adams, R. P. (2012) · 2012
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Structure discovery in nonparametric regression through compositional kernel search
Duvenaud, D., Lloyd, J. R., Grosse, R., Tenenbaum, J. B., and Ghahramani, Z. (2013) · 2013
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Wilson, A. G. and Nickisch, H. (2015) · 2015
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Improved stochastic trace estimation using mutually unbiased bases
Fitzsimons, J. K., Osborne, M. A., Roberts, S. J., and Fitzsimons, J. F. (2016) · 2016
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Scalable gaussian processes for characterizing multidimensional change surfaces
Herlands, W., Wilson, A., Nickisch, H., Flaxman, S., Neill, D., Van Panhuis, W., and Xing, E. (2016) · 2016
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Xu, Y., Xu, Y., and Saria, S. (2016) · 2016
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Personalized risk scoring for critical care prognosis using mixtures of gaussian processes
Alaa, A. M., Yoon, J., Hu, S., and van der Schaar, M. (2017) · 2017
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Sparse multi-output gaussian processes for medical time series prediction
Cheng, L.-F., Darnell, G., Chivers, C., Draugelis, M. E., Li, K., and Engelhardt, B. E. (2017) · 2017
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Scalable log determinants for gaussian process kernel learning
Dong, K., Eriksson, D., Nickisch, H., Bindel, D., and Wilson, A. G. (2017) · 2017
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Gpflow: A gaussian process library using tensorflow
Matthews, A. G. d. G., van der Wilk, M., Nickson, T., Fujii, K., Boukouvalas, A., León-Villagrá, P., Ghahramani, Z., and Hensman, J. (2017) · 2017
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Fast estimation of tr (f (a)) via stochastic lanczos quadrature
Ubaru, S., Chen, J., and Saad, Y. (2017) · 2017
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