Incremental Variational Sparse Gaussian Process Regression
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[1] Neil D. Lawrence,et al. Gaussian Processes for Big Data , 2013, UAI.
[2] Roni Khardon,et al. Sparse Variational Inference for Generalized GP Models , 2015, ICML.
[3] Zoubin Ghahramani,et al. Sparse Gaussian Processes using Pseudo-inputs , 2005, NIPS.
[4] Inderjit S. Dhillon,et al. Clustering with Bregman Divergences , 2005, J. Mach. Learn. Res..
[5] Zoubin Ghahramani,et al. Local and global sparse Gaussian process approximations , 2007, AISTATS.
[6] Pascal Fua,et al. Kullback-Leibler Proximal Variational Inference , 2015, NIPS.
[7] Yuesheng Xu,et al. Universal Kernels , 2006, J. Mach. Learn. Res..
[8] Matthew D. Hoffman,et al. A trust-region method for stochastic variational inference with applications to streaming data , 2015, ICML.
[9] Yuan Qi,et al. Sparse-posterior Gaussian Processes for general likelihoods , 2010, UAI.
[10] Aníbal R. Figueiras-Vidal,et al. Inter-domain Gaussian Processes for Sparse Inference using Inducing Features , 2009, NIPS.
[11] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[12] Lehel Csató,et al. Sparse On-Line Gaussian Processes , 2002, Neural Computation.
[13] Neil D. Lawrence,et al. Sparse Convolved Gaussian Processes for Multi-output Regression , 2008, NIPS.
[14] Carl E. Rasmussen,et al. A Unifying View of Sparse Approximate Gaussian Process Regression , 2005, J. Mach. Learn. Res..
[15] Shun-ichi Amari,et al. Natural Gradient Works Efficiently in Learning , 1998, Neural Computation.
[16] Chong Wang,et al. Stochastic variational inference , 2012, J. Mach. Learn. Res..
[17] Alexander Shapiro,et al. Stochastic Approximation approach to Stochastic Programming , 2013 .
[18] Neil D. Lawrence,et al. Fast Forward Selection to Speed Up Sparse Gaussian Process Regression , 2003, AISTATS.
[19] Michalis K. Titsias,et al. Variational Learning of Inducing Variables in Sparse Gaussian Processes , 2009, AISTATS.
[20] Stefan Schaal,et al. Incremental Local Gaussian Regression , 2014, NIPS.
[21] Neil D. Lawrence,et al. Efficient Multioutput Gaussian Processes through Variational Inducing Kernels , 2010, AISTATS.
[22] Kian Hsiang Low,et al. A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data , 2015, ICML.
[23] Sayan Mukherjee,et al. The Information Geometry of Mirror Descent , 2013, IEEE Transactions on Information Theory.
[24] Irina Holmes,et al. The Gaussian Radon Transform and Machine Learning , 2013, 1310.4794.
[25] Le Song,et al. Scalable Bayesian Inference via Particle Mirror Descent , 2015, ArXiv.
[26] Bernhard Schölkopf,et al. Sparse multiscale gaussian process regression , 2008, ICML '08.
[27] James Hensman,et al. On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes , 2015, AISTATS.
[28] Peter Kulchyski. and , 2015 .