### KuLSIF: Kernel-based Unconstrained Least-Squares Importance Fitting

*KuLSIF* is a kernel-based learning algorithm to directly estimate the ratio of two density functions without going
through density estimation.

R implementation of KuLSIF:
- kernelDRest.r computes kernel-based uLSIF (KuLSIF).
required library: "kernlab".

"snow" is available for parallel computing.

### Robust Parameter Fitting using Scoring Rules

This code is supplementary material for

T. Kanamori, H, Fujisawa:
"Robust Estimation under Heavy Contamination using Unnormalized Models", in Biometrika.

R implementation:

Go to Kanamori's web site