TY - GEN
T1 - Gaussian processes for Bayesian classification via Hybrid Monte Carlo
AU - Barber, David
AU - Williams, Christopher K. I.
N1 - Copyright of the Massachusetts Institute of Technology Press (MIT Press)
PY - 1997/5
Y1 - 1997/5
N2 - The full Bayesian method for applying neural networks to a prediction problem is to set up the prior/hyperprior structure for the net and then perform the necessary integrals. However, these integrals are not tractable analytically, and Markov Chain Monte Carlo (MCMC) methods are slow, especially if the parameter space is high-dimensional. Using Gaussian processes we can approximate the weight space integral analytically, so that only a small number of hyperparameters need be integrated over by MCMC methods. We have applied this idea to classification problems, obtaining excellent results on the real-world problems investigated so far.
AB - The full Bayesian method for applying neural networks to a prediction problem is to set up the prior/hyperprior structure for the net and then perform the necessary integrals. However, these integrals are not tractable analytically, and Markov Chain Monte Carlo (MCMC) methods are slow, especially if the parameter space is high-dimensional. Using Gaussian processes we can approximate the weight space integral analytically, so that only a small number of hyperparameters need be integrated over by MCMC methods. We have applied this idea to classification problems, obtaining excellent results on the real-world problems investigated so far.
KW - Bayesian method
KW - neural networks
KW - structure for the net
KW - integrals
KW - Markov Chain Monte Carlo
KW - weight space integral
UR - http://www.scopus.com/inward/record.url?scp=0000308194&partnerID=8YFLogxK
UR - http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=3990
M3 - Conference publication
SN - 0262100657
VL - 9
T3 - Proceeding of 1996 conference
SP - 340
EP - 346
BT - Advances in Neural Information Processing Systems
A2 - Mozer, M. C.
A2 - Jordan, M. I.
A2 - Petsche, T.
PB - MIT
CY - Cambridge, US
T2 - 10th Annual Conference on Neural Information Processing Systems, NIPS 1996
Y2 - 2 December 1996 through 5 December 1996
ER -