Accordion: A Trainable Simulator for Long-Term Interactive Systems-Reference-Cited by-同舟云学术

Accordion: A Trainable Simulator for Long-Term Interactive Systems

Published:2021-09-13 Issue: Volume: Page:
ISSN:
Container-title:Fifteenth ACM Conference on Recommender Systems
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Author:

McInerney James¹,Elahi Ehtsham²,Basilico Justin²,Raimond Yves²,Jebara Tony³

Affiliation:

1. Netflix Research, United States

2. Netflix, United States

3. Spotify, United States

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3460231.3474259

Reference27 articles.

1. The use of simulation in studying information storage and retrieval systems

2. Alex Boyd Robert Bamler Stephan Mandt and Padhraic Smyth. 2020. User-dependent neural sequence models for continuous-time event data. In Advances in Neural Information Processing Systems Vol. 33. 21488–21499. Alex Boyd Robert Bamler Stephan Mandt and Padhraic Smyth. 2020. User-dependent neural sequence models for continuous-time event data. In Advances in Neural Information Processing Systems Vol. 33. 21488–21499.

3. Simulating simple user behavior for system effectiveness evaluation

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