200 search results - page 15 / 40 » Approximating Gaussian Processes with H2-Matrices |
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...
TIP
2011
13 years 2 months ago
2011
—We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson–Gau...
NIPS
2004
13 years 9 months ago
2004
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
CGF
2010
13 years 4 months ago
2010
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...