InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models-Reference-Cited by-同舟云学术

InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models

Published:2023-09-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 17th ACM Conference on Recommender Systems
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Author:

Nagrecha Kabir¹^ORCID,Liu Lingyi²^ORCID,Delgado Pablo²^ORCID,Padmanabhan Prasanna²^ORCID

Affiliation:

1. Computer Science & Engineering, University of California, San Diego, USA

2. Machine Learning Platform, Netflix, Inc., USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3604915.3608778

Reference69 articles.

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3. Justin Boyan and Andrew Moore . 1994. Generalization in reinforcement learning: Safely approximating the value function. Advances in neural information processing systems 7 ( 1994 ). Justin Boyan and Andrew Moore. 1994. Generalization in reinforcement learning: Safely approximating the value function. Advances in neural information processing systems 7 (1994).

4. Wide & Deep Learning for Recommender Systems

5. The i486 CPU: executing instructions in one clock cycle

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