Sparse Online Gaussian Processes
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[1] G. Wahba,et al. Some results on Tchebycheffian spline functions , 1971 .
[2] G. Wahba. Spline models for observational data , 1990 .
[3] John C. Platt. A Resource-Allocating Network for Function Interpolation , 1991, Neural Computation.
[4] J. Freidman,et al. Multivariate adaptive regression splines , 1991 .
[5] Carl E. Rasmussen,et al. In Advances in Neural Information Processing Systems , 2011 .
[6] David Lowe,et al. Tracking of non-stationary time-series using resource allocating RBF networks , 1996 .
[7] Opper. On-line versus Off-line Learning from Random Examples: General Results. , 1996, Physical review letters.
[8] M. Gibbs,et al. Efficient implementation of gaussian processes , 1997 .
[9] L. Eon Bottou. Online Learning and Stochastic Approximations , 1998 .
[10] Manfred Opper,et al. Finite-Dimensional Approximation of Gaussian Processes , 1998, NIPS.
[11] David Barber,et al. Bayesian Classification With Gaussian Processes , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[12] David Saad,et al. On-Line Learning in Neural Networks , 1999 .
[13] Hidemitsu Ogawa,et al. RKHS-based functional analysis for exact incremental learning , 1999, Neurocomputing.
[14] Matthias W. Seeger,et al. Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers , 1999, NIPS.
[15] Gunnar Rätsch,et al. Input space versus feature space in kernel-based methods , 1999, IEEE Trans. Neural Networks.
[16] David Haussler,et al. Probabilistic kernel regression models , 1999, AISTATS.
[17] Michael E. Tipping. The Relevance Vector Machine , 1999, NIPS.
[18] Ole Winther,et al. Efficient Approaches to Gaussian Process Classification , 1999, NIPS.
[19] Noel A Cressie,et al. Long-Lead Prediction of Pacific SSTs via Bayesian Dynamic Modeling , 2000 .
[20] Volker Tresp,et al. A Bayesian Committee Machine , 2000, Neural Computation.
[21] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[22] Bernhard Schölkopf,et al. Sparse Greedy Matrix Approximation for Machine Learning , 2000, International Conference on Machine Learning.
[23] Christopher K. I. Williams,et al. Using the Nyström Method to Speed Up Kernel Machines , 2000, NIPS.
[24] Lemm,et al. Bayesian approach to inverse quantum statistics , 2000, Physical review letters.
[25] Dan Cornford,et al. Structured neural network modelling of multi-valued functions for wind vector retrieval from satellite scatterometer measurements , 2000, Neurocomputing.
[26] Gert Cauwenberghs,et al. Incremental and Decremental Support Vector Machine Learning , 2000, NIPS.
[27] M. Opper,et al. Gaussian processes and SVM: Mean field results and leave-one-out , 2000 .
[28] Tom Minka,et al. Expectation Propagation for approximate Bayesian inference , 2001, UAI.
[29] Manfred Opper,et al. A Bayesian Approach to Online Learning , 2006 .
[30] A. P. Dawid,et al. Regression and Classification Using Gaussian Process Priors , 2009 .