REVEAL 2019: Reinforcement and Robust Estimators for Recommendation

Workshop at ACM RecSys 2019, Copenhagen, Denmark
September 20, 2019
https://sites.google.com/view/reveal2019/

State-of-the-art recommender systems are notoriously hard to design and improve 
upon due to their interactive and dynamic nature. They involve a multi-step 
decision-making process, where a stream of interactions occurs between the user 
and the system. Leveraging reward signals from these interactions and creating 
a scalable and performant recommendation inference model is a key challenge. 
Traditionally, interactions have often been viewed as independent to make the 
problem tractable. But in order to improve recommender systems further, models 
will need to take into account the delayed effects of each recommendation and 
start reasoning/planning for longer-term user satisfaction. To this end, our 
workshop invites contributions that enable recommender systems to adapt 
effectively to diverse forms of user feedback and to optimize the quality of 
each user's long-term experience.

More broadly, we invite submissions of extended abstracts (max 2 pages) on the 
following and related topics:
- Reinforcement learning and bandits for recommendation
- Robust estimators, counterfactual and off-policy evaluation
- Causal recommender systems
- Using simulation for recommender systems evaluation
- New evaluation datasets
- New offline metrics for recommender systems

Accepted contributions will be presented as talks or posters. The reviews will 
be single-blind.

Submission deadline: August 1, 2019 via 
https://cmt3.research.microsoft.com/REVEAL2019.

Organizers:
- Thorsten Joachims, Information Science and Computer Science, Cornell 
University
- Adith Swaminathan, Deep Learning Technology Center, Microsoft Research
- Maria Dimakopoulou and Yves Raimond, R&D, Netflix
- Olivier Koch and Flavian Vasile, R&D, Criteo
---
Thorsten Joachims
Professor, Cornell University
Department of Computer Science
Department of Information Science
http://www.joachims.org/<https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.joachims.org%2F&data=02%7C01%7CPaul.N.Bennett%40microsoft.com%7C385a5152b044470ef88a08d5ecb4507e%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C636675181544353943&sdata=A1yy3svoKEgicKO%2FXDF82JB5WpOM9yBZyyFv209OjSg%3D&reserved=0>

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