13 October 2009

Machine Learning While I Work

I am setting up Postfix so I have spare time as I try things out. This post is about the things I am reading or watching in the background.

Taskforce on Context-Aware Computing
I went to a lecture called  Open Mobile Miner (OMM): A System for Real Time Mobile Data Analysis. There is a video here, a description of OMM here and lecture slides here (pdf).

Shonali Krishnaswamy's group are making software that does some analysis of data on a smart phone before uploading it, thereby reducing the phone's power consumption by reducing communications. Their examples include ECG output, traffic congestion metrics and taxi location data. The data in their examples is scalar and sampled at 0.5 Hz or less so it is hard to see why a simple store-and-forward scheme would not achieve much the same thing. I guess I need to read their publications more deeply.

Statistical Learning as the Ultimate Agile Development Tool
by Peter Norvig is an overview of modern practical machine learning. The summary is focus on the data, not the code.

Learning Theory
by Mark Reid was an introduction to some theoretical aspects of machine learning presented in a summer school in Canberra in January 2009.

Now some videos of how machine learning can be applied to models of the face.

Changes of facial features on the of dominance, trustworthiness and competence dimensions in a computer model developed by Oosterhof & Todorov (2008).

Now it is time to start watching a video on distributed computing

Swarm: Distributed Computation in the Cloud from Ian Clarke on Vimeo.