“Deep Neural Networks for YouTube Recommendations”, Paul Covington, Jay Adams, Emre Sargin2016-09-15 (retrieval AI, model-free RL)⁠:

YouTube represents one of the largest scale and most sophisticated industrial recommendation systems in existence.

In this paper, we describe the system at a high level and focus on the dramatic performance improvements brought by deep learning.

The paper is split according to the classic two-stage information retrieval dichotomy: first, we detail a deep candidate generation model and then describe a separate deep ranking model [since upgraded to REINFORCE].

We also provide practical lessons and insights derived from designing, iterating and maintaining a massive recommendation system with enormous user-facing impact.

[Keywords: recommender system, deep learning, scalability]