Machine Learning in Microsoft's Online Services: TrueSkill, AdPredictor, and Matchbox

author: Thore Graepel, Microsoft Research, Cambridge, Microsoft Research
published: Nov. 16, 2010,   recorded: September 2010,   views: 6341
Categories

See Also:

Download slides icon Download slides: ecmlpkdd2010_graepel_mlm_01.pdf (3.9 MB)


Help icon Streaming Video Help

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Machine Learning plays a crucial role in Microsoft's online services. In this talk, I will describe three powerful applications of machine learning.

TrueSkill is Xbox Live's Ranking and Matchmaking system and ensures that gamers online have balanced and exciting matches with equally skilled opponents. AdPredictor is the system that estimates click-through rates (CTR) for ad selection and pricing within Microsoft's search engine Bing. Matchbox is a large scale Bayesian recommender system that combines aspects of collaborative filtering and content-based recommendation. It is currently being used for tweet recommendation within projectemporia.com.

All three systems have in common that they are based on techniques from graphical models and approximate Bayesian inference, yet operate at large scale. I will discuss the underlying models and algorithms as well as application-specific insights and findings. Time permitting, I will show the three systems in action. This is based on joint work with Ralf Herbrich, David Stern, Thomas Borchert, Tom Minka, and Joaquin Quiñonero Candela.TrueSkill is Xbox Live's Ranking and Matchmaking system and ensures that gamers online have balanced and exciting matches with equally skilled opponents.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: