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Expo Workshop
Real World RL: Azure Personalizer & Vowpal Wabbit
Sheetal Lahabar · Etienne Kintzler · Mark Rucker · Bogdan Mazoure · Qingyun Wu · Pavithra Srinath · Jack Gerrits · Olga Vrousgou · John Langford · Eduardo Salinas

Sun Jul 18 05:00 AM -- 09:30 AM (PDT) @

The theme of this workshop will be real world applications of reinforcement learning. We will give a demo/tutorial of the latest features and additions to Azure Personalizer, an award winning and easy to use RL cloud service (https://azure.microsoft.com/en-us/services/cognitive-services/personalizer/). The first release of Personalizer was presented in an ICML 2019 workshop. We will present the latest additions to the service, including multi-slot personalization.

We will demonstrate how to leverage the latest release of Vowpal Wabbit, an open source machine learning library (https://vowpalwabbit.org/). It provides fast, scalable machine learning and has unique capabilities such as learning to search, active learning, contextual memory, and extreme multiclass learning. It has a focus on reinforcement learning and provides production ready implementations of Contextual Bandit algorithms.

This part will include:

- Demo on COBA - benchmarking framework for CB algorithms (https://github.com/VowpalWabbit/coba)
- Using Panda Dataframes with pyVW
- AutoML & pyVW
- Hands on demo of continuous actions with VW
- Integrating VW with Apache Spark

Author Information

Sheetal Lahabar
Etienne Kintzler (-)
Mark Rucker
Bogdan Mazoure (MILA,McGill University)
Qingyun Wu
Pavithra Srinath (Microsoft Research)
Jack Gerrits
Olga Vrousgou (Microsoft Research)
John Langford (Microsoft Research)
Eduardo Salinas (Microsoft)

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