Useful Control Variates for Variance Reduction

Motivation

For many problems in machine learning (ranging from Generative Models to Reinforcement Learning), we rely on Monte Carlo estimators of gradients for optimization. Often, the noise in our gradient estimators is a major nuisance factor affecting how close we can get to local optima.

There are many tricks around the corner to improve on this issue. A popular one is the “bias removal trick” widely known in the Reinforcement Learning literature.

Many – if not all – of these tricks are particular cases of what is known as a control variate ( link1, link2, link3 ) a very generic method for variance reduction.

In this post I will try to characterize a few interesting and potentially useful applications of control variates and discuss their limitations.

 

img1

img2

img3

 

If you happen to know more interesting facts, theorems or use cases of control variates please let me know.

The pdf source of this post can be found here.

 

 

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s