Blog posts and Summer gigs
I have recently heard complaints that this blog is rather quiet lately. I agree. I have definitely been focused on publishing through other sources and have found little time to write interesting t...
I have recently heard complaints that this blog is rather quiet lately. I agree. I have definitely been focused on publishing through other sources and have found little time to write interesting t...
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 focused on rating prediction, ranking is...
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. This conference was mostly organized by Fac...
(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 post like this. I hope you bear with me...
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 Recsys Conference. I have been attending th...
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, Recsys has become my favorite conferen...
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. This was one of the preferred discussion...
Last week, I published a post on the Netflix tech blog. The post, entitled “Netflix Recommendations: Beyond the 5 stars” describes how recommendations have evolved at Netflix since the Netflix Priz...
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 very interesting talks from companies s...
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 problem is formulated as the finding of a uti...