Industry Session 2: Interesting Domains

Date: Tuesday, Aug 29, 2017, 14:00-15:45
Location: Main Room
Chair: Alan Said

Justin BasilicoYves Raimond

Déjà Vu: The Importance of Time and Causality in Recommender Systems

by Justin Basilico  (Netflix) and Yves Raimond (Netflix)

Time plays a key role in recommendation. Handling it properly is especially critical when using recommender systems in real-world applications, which may not be as clear when doing research with historical data. In this talk, we will discuss some of the important challenges of handling time in recommendation algorithms at Netflix. We will focus on challenges related to how our users, items, and systems all change over time. We will then discuss some strategies for tackling these challenges, which revolves around proper treatment of causality in our systems.

About the Speakers

Justin Basilico is a Research/Engineering Manager for Page Algorithms Engineering at Netflix. He leads an applied research team focused on developing the next generation of algorithms used to generate the Netflix homepage through machine learning, ranking, recommendation, and large-scale software engineering. He has also developed machine learning approaches that yielded significant improvements in the personalized ranking algorithms that drive the Netflix recommendation system. Prior to Netflix, he worked on machine learning in the Cognitive Systems group at Sandia National Laboratories. He is also the co-creator of the Cognitive Foundry, an open-source software library for building machine learning algorithms and applications.

Yves Raimond is a Research/Engineering Director at Netflix, where he leads the Search, Targeting & Recommendations Algorithm Engineering team: a mixed team of researchers and engineers building the next generation of Machine Learning algorithms used to drive the Netflix experience. Before that, he was a Lead Research Engineer in BBC R&D, working on information extraction from Multimedia content. He holds a PhD from Queen Mary, University of London.

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