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We present Blitzkriging, a new approach to fast inference for Gaussian processes, applicable to regression, optimisation and classification.
Efficient descriptor-vector multiplications in stochastic automata networks
Paulo Fernandes, Brigitte Plateau, and William J. Stewart · 1998
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Discovering hidden features with gaussian processes regression
F Vivarelli and C. K.I Williams · 1999
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Random forests
Leo Breiman · 2001
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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Carl Edward Rasmussen and Christopher K. I. Williams · 2005
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Probabilistic non-linear principal component analysis with Gaussian process latent variable models
Neil Lawrence · 2005
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A unifying view of sparse approximate Gaussian process regression
Joaquin Quiñonero Candela and Carl Edward Rasmussen · 2005
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Variational learning of inducing variables in sparse Gaussian processes
Michalis K. Titsias · 2009
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Wind power density forecasting using ensemble predictions and time series models
J.W. Taylor, P.E. McSharry, and R. Buizza · 2009
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Sparse-spectrum Gaussian process regression
Miguel Laz̀aro-Gredilla, Joaquin Quinõnero Candela, Carl Edward Rasmussen, and Aníbal R. Figueiras-Vidal · 2010
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Scalable Inference for Structured Gaussian Process Models
Yunus Saatçi · 2011
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Remark on ‘algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization’
José Luis Morales and Jorge Nocedal · 2011
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Local and global learning methods for predicting power of a combined gas and steam turbine
Heysem Kaya, Pınar Tüfekci, and Sadık Fikret Gürgen · 2012
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ADADELTA: an adaptive learning rate method
Matthew D. Zeiler · 2012
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GPatt: Fast multidimensional pattern extrapolation with Gaussian processes
Variational inference for mahalanobis distance metrics in gaussian process regression
Michalis Titsias and Miguel Lazaro-Gredilla · 2013
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Variational Inference for Gaussian Process Modulated Poisson Processes
C. Lloyd, T. Gunter, M. A. Osborne, and S. J. Roberts · 2014
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Fast kernel learning for multidimensional pattern extrapolation
Andrew Gordon Wilson, Elad Gilboa, Arye Nehorai, and John P. Cunningham · 2014
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GPy: A Gaussian process framework in python
The GPy authors · 2014
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Kernel interpolation for scalable structured gaussian processes (KISS-GP)
Andrew Gordon Wilson and Hannes Nickisch · 2015
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Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs
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Andrew Gordon Wilson, Elad Gilboa, Arye Nehorai, and John P Cunningham · 2013
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Gaussian processes for big data
James Hensman, Nicoló Fusi, and Neil D. Lawrence · 2013
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Distributed gaussian processes
MP Deisenroth and JW Ng
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Y. Gal and R. Turner · 2015
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A unifying framework of anytime sparse Gaussian process regression models with stochastic variational inference for big data
Trong Nghia Hoang, Quang Minh Hoang, and Bryan Kian Hsiang Low · 2015
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