Recommendations as Personalized Learning to Rank
As I have explained in other publications such as the Netflix Techblog, ranking is a very important part of a Recommender System. Although the Netflix Prize ...
Recent Posts
Tools for Data Processing @ Webscale
A couple of days ago, I attended the Analytics @Webscale workshop at Facebook. I found this workshop to be very interesting from a technical perspective. Thi...
10 Little lessons for life that I learned from running
(Sorry for allowing myself to depart from the usual geeky computer science algorithmic talk in this blog. I owed it to myself and my biggest hobby to write a...
Recsys 2012: A long (and likely biased) summary
After a great week in beautiful and sunny Dublin (yes, sunny), it is time to look back and recap on the most interesting things that happened in the 2012 Rec...
Netflix @ Recsys 2012
We are just a few days away from the 2012 ACM Recommender Systems Conference (#Recsys2012), that this year will take place in Dublin, Ireland. Over the years...
More data or better models?
The discussion of whether it is better to focus on building better algorithms or getting more data is by no means new. But, it is really catching on lately. ...
Beyond the 5 Stars Round up
Last week, I published a post on the Netflix tech blog. The post, entitled “Netflix Recommendations: Beyond the 5 stars” describes how recommendations have e...
Recsys 2011 – Notes and Pointers
I found Recsys this year of very high quality in general. There were many good papers and presentations. The Industry track was also very high-quality, with...
The Recommender Problem & the Presentation Context
In the traditional formulation of the “Recommender Problem”, we have pairs of items and users and user feedback values for very few of those dyads. The probl...
Joining Netflix
Three weeks ago, I started to work for Netflix. Everything has moved so fast with so many things to do and learn that it seems like I have already been here ...