Figure 1. Convergence comparison between VB and PX-VB for ARD regression on synthetic data (a) and gene expression data (b).
We compare the convergence speed of VB and PX-VB for the ARD model on
both synthetic
data and gene expression data. The synthetic data are sampled from the
sinc function
with added Gaussian noise. We use RBF kernels for the feature expansion
n with kernel
width 3. VB and PX-VB provide
basically
identical fitting to the data. For gene expression data, we apply ARD
to
analyze the relationship
between binding motifs and the expression of their target genes. For
this task, we use the third
order polynomial kernels.
The results of convergence comparison are shown in figure 1. With a
little modification
of VB updates, we increase the convergence speed significantly.
Figure 1. Convergence comparison between VB and PX-VB for ARD regression on synthetic data (a) and gene expression data (b). |