Matlab Kernel Toolbox

The KERN software can be downloaded here.

Release Information

Current release is 0.167.

As well as downloading the KERN software you need to obtain the toolboxes specified below.

Toolbox	Version
OPTIMI	0.132
NDLUTIL	0.157
NETLAB	3.3

Added 'translate' kernel which allows wrapping of other kernels with a kernel that translates the input location. Useful for moving the non-stationarity around the input space.

Version 0.166

Added periodic version of RBF kernel (see Rasmussen and Williams pg 92 or Mackay's introduction to GPs (1998)) and periodic version of Gibbs's non-statinary kernel (see e.g. pg 93 of Rasmussen and Williams).

Version 0.165

Added flag which indicates whether or not a kernel is stationary. This can be used for speeding computations (stationary kernels have a constant diagonal). Also replaced calls to constraining functions with 'optimiDefaultConstraint' calls which return the default constraint (making it easier for the user to change).

Version 0.163

This release removes the stubs for several KernDiagGradX.m files, which were confusing kernDiagGradX.m, which assumes they only exist if the function is implemented. For the kernel types 'lin', 'poly', 'mlp', and their 'ard' counter-types, these files existed but weren't yet implemented.

Version 0.162

Added the Gibbs's non-stationary kernel, the rational quadratic kernel and the Matern kernel with nu = 3/2 and nu = 5/2.

Verison 0.161

Introduced the single input motif kernel for the GPSIM toolbox. Also there is much more documentation, and a new file kernelGenerator.py for creating the basic files for your own kernels.

Examples

This toolbox allows computation of several different kernels and their gradients. You can add kernels to the toolbox by creating versions of the relevant files. Once added, they can be tested using the kernTest. For example you can test the RBF kernel by writing

>> kernTest('rbf')

There are several kernels implemented, the ones that are being maintained for the latest release are:

gibbs gibbsperiodic lin linard rbf rbfard rbfperiodic matern32 matern52 ratquad mlp mlpard poly polyard sim white whitefixed bias cmpnd tensor (tensor kernels). file (a kernel written in a file).

A new kernel can be created using the compound kernel, cmpnd or the tensor kernel, tensor. The compound kernel is made up of sums of individual kernels. Most often you will need to create a kernel containing a base kernel (e.g. rbf) and adding a white noise kernel, white and perhaps a constant offset through the bias kernel bias. On initialisation most kernel parameters are set to 1. Exceptions are ARD scale parameters, the variance of the white and bias kernels and the weight and bias variances of the mlp kernels.