Kernel Adaptive Metropolis-Hastings

Joint measures and cross-covariance operators

Baker, C · 1973

Earlier work this paper cites.

Efficient Metropolis jumping rules

Gelman, A., Roberts, G. O., and Gilks, W. R · 1996

Earlier work this paper cites.

Integral transforms, reproducing kernels, and their applications

Saitoh, S · 1997

Earlier work this paper cites.

Nonlinear component analysis as a kernel eigenvalue problem

Schölkopf, B., Smola, A. J., and Müller, K.-R · 1998

Earlier work this paper cites.

Bayesian classification with Gaussian processes

Williams, C.K.I. and Barber, D · 1998

Earlier work this paper cites.

Adaptive Proposal Distribution for Random Walk Metropolis Algorithm

Haario, H., Saksman, E., and Tamminen, J · 1999

Earlier work this paper cites.

An adaptive Metropolis algorithm

Haario, H., Saksman, E., and Tamminen, J · 2001

Earlier work this paper cites.

Regularized principal manifolds

Smola, A. J., Mika, S., Schölkopf, B., and Williamson, R. C · 2001

Earlier work this paper cites.

Learning to find pre-images

Bakir, G., Weston, J., and Schölkopf, B · 2003

Earlier work this paper cites.

Langevin diffusions and Metropolis-Hastings algorithms

Roberts, G.O. and Stramer, O · 2003

Cited alongside, same era.

Reproducing Kernel Hilbert Spaces in Probability and Statistics

Berlinet, A. and Thomas-Agnan, C · 2004

Cited alongside, same era.

Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces

Fukumizu, K., Bach, F. R., and Jordan, M. I · 2004

Cited alongside, same era.

Integrating structured biological data by kernel maximum mean discrepancy

Borgwardt, K. M., Gretton, A., Rasch, M. J., Kriegel, H.-P., Schölkopf, B., and Smola, A. J · 2006

Cited alongside, same era.

A kernel method for the two-sample problem

Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B., and Smola, A · 2007

Cited alongside, same era.

Coupling and ergodicity of adaptive Markov chain Monte Carlo algorithms

Roberts, G.O. and Rosenthal, J.S · 2007

The pseudo-marginal approach for efficient Monte Carlo computations

Andrieu, C. and Roberts, G.O · 2009

Later among the works it cites.

Hilbert space embeddings and metrics on probability measures

Sriperumbudur, B., Gretton, A., Fukumizu, K., Lanckriet, G., and Schölkopf, B · 2010

Later among the works it cites.

Riemann manifold Langevin and Hamiltonian Monte Carlo methods

Girolami, M. and Calderhead, B · 2011

Later among the works it cites.

Universality, characteristic kernels and RKHS embedding of measures

Sriperumbudur, B., Fukumizu, K., and Lanckriet, G · 2011

Later among the works it cites.

Bayesian learning via stochastic gradient Langevin dynamics

Welling, M. and Teh, Y.W · 2011

Later among the works it cites.

Slice sampling covariance hyperparameters of latent Gaussian models

Murray, I. and Adams, R.P · 2012

Later among the works it cites.