Jeremy Stober put together a great set of notes on Gaussian processes for reinforcement learning. The notes are very clear and easy to follow. You can find them here.

## Posts Tagged ‘Gaussian Process’

### Wednesday 04/07/2010

April 28, 2010### Wednesday 03/31/2010

April 7, 2010### Wednesday 03/24/2010

March 24, 2010Meghana began covering Gaussian processes for classification. You can find the notes here.

### Stochastic Process notes

March 23, 2010Priyank is still working the latex notes. In the meantime, here are the scanned notes from those meetings.

### Wednesday 03/03/2010, 03/10/2010

March 8, 2010We began discussion of Gaussian Processes for regression.

I am going to try uploading the presenter’s notes directly. You can find the notes for this week here and here.

Next week (after spring break), we will move on to Gaussian Processes for classification. We will cover the end of chapter 2 in some detail in a couple of weeks.

We need a volunteer to cover MCMC for GP’s. This paper on slice sampling was recommended.

### Wednesday 02/10/2010, 02/17/2010, 02/24/2010

February 16, 2010Priyank discussed some basic measure theory in preparation for our discussion on Gaussian processes. Next week, we will discuss how stochastic processes such as the Gaussian process arise from basic concepts.

There will be no weekly scribe notes during the series on basic theory. Instead, I will post a comprehensive set of scribe notes (with references) after we are done.

**EDIT:** We spent three meetings discussing general stochastic processes. I will post notes once they are avaliable.

### Wednesday 02/03/2010

February 9, 2010Definition (Rasmussen):A Gaussian process is a collection of random variables, any finite number of which have (consistent) Gaussian distributions.