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To scale Gaussian processes (GPs) to large data sets we introduce the robust Bayesian Committee Machine (rBCM), a practical and scalable product-of-experts model for large-scale distributed GP regression.
A Multiplicative Formula for Aggregating Probability Assessments
Bordley, Robert F · 1982
Earlier work this paper cites.
Adaptive Mixtures of Local Experts
Jacobs, Robert A., Jordan, Michael I., Nowlan, Steven J., and Hinton, Geoffrey E · 1991
Earlier work this paper cites.
Statistics for Spatial Data
Cressie, Noel A. C · 1993
Earlier work this paper cites.
Selecting Weighting Factors in Logarithmic Opinion Pools
Heskes, Tom · 1998
Earlier work this paper cites.
Efficient Global Optimization of Expensive Black-Box Functions
Jones, Donald R., Schonlau, Matthias, and Welch, William J · 1998
Earlier work this paper cites.
A Bayesian Committee Machine
Tresp, Volker · 2000
Earlier work this paper cites.
Using the Nyström Method to Speed up Kernel Machines
Williams, Christopher K.I. and Seeger, Matthias · 2001
Earlier work this paper cites.
Infinite Mixtures of Gaussian Process Experts
Rasmussen, Carl E. and Ghahramani, Zoubin · 2002
Earlier work this paper cites.
Fast Forward Selection to Speed up Sparse Gaussian Process Regression
Seeger, Matthias, Williams, Christopher K. I., and Lawrence, Neil D · 2003
Earlier work this paper cites.
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models
Lawrence, Neil · 2005
Earlier work this paper cites.
A Unifying View of Sparse Approximate Gaussian Process Regression
Quiñonero-Candela, Joaquin and Rasmussen, Carl E · 2005
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An Alternative Infinite Mixture of Gaussian Process Experts
Meeds, Edward and Osindero, Simon · 2006
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Gaussian Processes for Machine Learning
Rasmussen, Carl E. and Williams, Christopher K. I · 2006
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Fast Gaussian Process Regression Using KD-Trees
Shen, Yirong, Ng, Andrew Y., and Seeger, Matthias · 2006
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Sparse Gaussian Processes using Pseudo-Inputs
Snelson, Edward and Ghahramani, Zoubin · 2006
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Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
Krause, Andreas, Singh, Ajit, and Guestrin, Carlos · 2008
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Sparse Spectrum Gaussian Process Regression
Lázaro-Gredilla, Miguel, Quiñonero-Candela, Joaquin, Rasmussen, Carl E., and Figueiras-Vidal, Aníbal R · 2010
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Efficient Gaussian Process Inference for Short-Scale Spatio-Temporal Modeling
Luttinen, Jaakko and Ilin, Alexander · 2012
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A Framework for Evaluating Approximate Methods for Gaussian Process Regression
Chalupka, Krzysztof, Williams, Christopher K. I., and Murray, Iain · 2013
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Gaussian Processes for Data-Efficient Learning in Robotics and Control
Deisenroth, Marc P., Fox, Dieter, and Rasmussen, Carl E · 2013
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Gaussian Processes for Big Data
Hensman, James, Fusi, Nicolò, and Lawrence, Neil D · 2013
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Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions
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A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
Brochu, Eric, Cora, Vlad M., and de Freitas, Nando · 2009
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Variational Learning of Inducing Variables in Sparse Gaussian Processes
Titsias, Michalis K · 2009
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Variational Mixture of Gaussian Process Experts
Yuan, Chao and Neubauer, Claus · 2009
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Cao, Yanshuai and Fleet, David J · 2014
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Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models
Gal, Yarin, van der Wilk, Mark, and Rasmussen, Carl E · 2014
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Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression
Ng, Jun W. and Deisenroth, Marc P · 2014
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Fast Allocation of Gaussian Process Experts
Nguyen, Trung V. and Bonilla, Edwin V · 2014
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