Deep Learning Discussion: Recommender Systems

This is part of the series of bi-weekly deep learning discussions.  

Topic for this Meetup: Recommender Systems

We will look at deep learning applied to recommender systems, particularly to large-scale systems like YouTube. The recommendation problem is transformed into a ranking problem, where we can apply machine learning methods. Deep learning is essentially used as a complex supervised learning method.    

Below is our reading list this week.  

1. Covington, Paul, Jay Adams, and Emre Sargin. "Deep Neural Networks for YouTube Recommendations." In Proceedings of the 10th ACM Conference on Recommender Systems, pp. 191-198. ACM, 2016.

2. Cheng, Heng-Tze, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson et al. "Wide & Deep Learning for Recommender Systems." In Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, pp. 7-10. ACM, 2016.

This discussion will be led by Vish Ramamurti. 

See you at our meetup. 

6:30-7pm Meet and greet

7-8:30pm Main topic discussion, based on recommended reading

For more information please see: https://www.meetup.com/svaibdata/events/235177576/