Gaussian Mixture Kullback-Leibler Importance Estimation Procedure (GM-KLIEP)

Introduction

This method is an extention of the Kullback-Leibler importance estimation procedure (KLIEP), an importance estimation method using linear or kernel models. An advantage of GMMs is that covariance matrices can also be learned through an iterative procedure, so the proposed method — which we call the Gaussian mixture KLIEP (GM-KLIEP) — is expected to work well when the true importance function has high correlation.

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Examples (Toy data)

GM-KLIEP 
GM-KLIEP 

Acknowledgement

I am grateful to Prof. Masashi Sugiyama and Mr. Taketo Akama for their support in developing this software.

Contact

I am happy to have any kind of feedbacks. E-mail: yamada AT sg DOT cs DOT titech DOT ac DOT jp