Events and Updates

Curious what events and conferences we're attending? Find out here.

Recent Updates

NeurIPS 2018

Dec 10, 2018

Netflix was a proud sponsor of NeurIPS in Montreal this year. We were also able to sponsor WiML this year which provided a great opportunity to meet promising women and allies in the ML space. Here are some highlights from the conference:

Aish Fenton, a research manager for our recommendations platform, gave a talk at the System ML Workshop on why typed languages (such as Scala, Haskell, etc) are useful for machine learning. You can access the slides here

Dawen Liang, one of our machine learning scientists, along with colleagues from academia and industry, organized the 1st Symposium on Approximate Bayesian Inference (AABI), which is the spiritual successor of a series of successful NeurIPS AABI workshops in the past few years. It was a one-day event with invited talks from the top researchers describing their latest work, as well as contributed talks covering a broad area of the field. It was very well attended.

We were also able to submit several papers and posters this year:
Scalar Posterior Sampling with Applications, In Wed Poster Session B by Georgios Theocharous · Zheng Wen · Yasin Abbasi · Nikos Vlassis
Explaining Deep Learning Models -- A Bayesian Non-parametric Approach In Tue Poster Session B by Wenbo Guo · Sui Huang · Yunzhe Tao · Xinyu Xing · Lin Lin
Correlated Variational Auto-Encoders In Bayesian Deep Learning Workshop by Da Tang, Dawen Liang and Tony Jebara

Netflix at Qcon SF

Nov 7, 2018

We really enjoyed participating in QCon SF this year, and had speakers and host tracks from a number of different teams at Netflix. Here are a few highlights from our machine learning teams:

Ville Tuulos, an engineer on our machine learning infrastructure team, gave a talk about about human centric ML infrastructure. Many existing open-source machine learning frameworks are great at making advanced modeling possible. The job of our ML infrastructure is to make it remarkably easy to apply these frameworks to real business problems at Netflix. We have found that this requires an infrastructure that covers the day-to-day challenges of data scientists holistically, from understanding input data to building trust with consumers of models, not just the parts that are directly related to fitting and scoring models. He talked about the techniques and underlying principles driving our approach, which you'll be able to adapt and apply to your own use cases. You can view the slides here.

Justin Basilico, a research director for our page algorithms team, gave a talk on artwork personalization at Netflix. In this talk, he presented an approach for personalizing the artwork we show for each title on the Netflix homepage. He looks at how to frame this as a machine learning problem using contextual multi-armed bandits in a recommendation system setting. He also describes the algorithmic and system challenges involved in getting this type of approach for artwork personalization to succeed at Netflix scale. You can view the slides here.

Netflix sponsored the Women & Allies in Tech Breakfast, which was a great opportunity to network with smart women from different industries. We were pleased to hear that a portion of the sponsorship money provided will be used to grant QCon scholarships to 12 women and/or members of under-represented groups.