MCMC methods for Gaussian process models using fast approximations for the likelihood

Woodbury, M.A., (1950) “Inverting modified matrices”, Memorandum Rept. 42,

Original

1950

Earlier work this paper cites.

Metropolis, N. and Rosenbluth, A.W. and Rosenbluth, M.N. and Teller, A.H. and Teller, E. (1953) “Equations of State Calculations by Fast Computing Machines”, Journal of Chemical Physics

1953

Earlier work this paper cites.

Neal, R. M. (1993), “Probabilistic Inference Using Markov Chain Monte Carlo Methods”, Technical Report, Dept. of Computer Science, University of Toronto

1993

Earlier work this paper cites.

Neal, R. M. (1996) “Sampling from multimodal distributions using tempered transitions”, Statistics and Computing

1996

Earlier work this paper cites.

Neal, R. M. (1997), “Monte Carlo implementation of Gaussian process models for Bayesian regression and classification”, Technical Report, Dept. of Statistics, University of Toronto

1997

Cited alongside, same era.

Neal, R. M. (1998), “Regression and Classification Using Gaussian Process Priors”, Bernardo, J. M. (editor) Bayesian Statistics

1998

Cited alongside, same era.

Williams, C.K.I. and Seeger, M. (2001), “Using the Nyström Method to Speed up Kernel Machines”, Advances in Neural Information Processing Systems 13, pp. 682-688

2001

Cited alongside, same era.

Neal, R. M. (2003), “Slice sampling”, Annals of Statistics

2003

Cited alongside, same era.

Drineas, P. and Mahoney, M. (2005) “On the Nystrom Method for Approximating a Gram Matrix for Improved Kernel-Based Learning” Journal of Machine Learning Research

2005

Later among the works it cites.

Neal, R. M. (2006), “Constructing Efficient MCMC Methods Using Temporary Mapping and Caching”, Talk at Columbia University, December 2006 Available from http://www.utstat.utoronto.ca/

2006

Later among the works it cites.

Rasmussen, C. E. and Williams, C. K. I. (2006), Gaussian Process for Machine Learning

2006

Later among the works it cites.

Quiñonero-Candela, J., Rasmussen, C. E., and Williams, C. K. I. (2007), “Approximation Methods for Gaussian Process Regression”, Technical Report MSR-TR-2007-124

2007

Later among the works it cites.