User Response Models to Improve a REINFORCE Recommender System-Reference-Cited by-同舟云学术

User Response Models to Improve a REINFORCE Recommender System

Published:2021-03-08 Issue: Volume: Page:
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Container-title:Proceedings of the 14th ACM International Conference on Web Search and Data Mining
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Author:

Chen Minmin¹,Chang Bo¹,Xu Can¹,Chi Ed H.¹

Affiliation:

1. Google, Inc., Mountain View, CA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3437963.3441764

Reference55 articles.

1. Top-K Off-Policy Correction for a REINFORCE Recommender System

2. Minmin Chen Ramki Gummadi Chris Harris and Dale Schuurmans. 2019 b. Surrogate Objectives for Batch Policy Optimization in One-step Decision Making. In Advances in Neural Information Processing Systems. 8825--8835. Minmin Chen Ramki Gummadi Chris Harris and Dale Schuurmans. 2019 b. Surrogate Objectives for Batch Policy Optimization in One-step Decision Making. In Advances in Neural Information Processing Systems. 8825--8835.

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