Locality-Sensitive State-Guided Experience Replay Optimization for Sparse Rewards in Online Recommendation-Reference-Cited by-同舟云学术

Locality-Sensitive State-Guided Experience Replay Optimization for Sparse Rewards in Online Recommendation

Published:2022-07-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Chen Xiaocong¹,Yao Lina¹,McAuley Julian²,Guan Weili³,Chang Xiaojun⁴,Wang Xianzhi⁴

Affiliation:

1. University of New South Wales, Sydney, NSW, Australia

2. University of California, San Diego, San Diego, CA, USA

3. Monash University, Melbourne, VIC, Australia

4. University of Technology Sydney, Sydney, NSW, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477495.3532015

Reference42 articles.

1. Marcin Andrychowicz , Filip Wolski , Alex Ray , Jonas Schneider , Rachel Fong , Peter Welinder , Bob McGrew , Josh Tobin , Open AI Pieter Abbeel , and Wojciech Zaremba . 2017 . Hindsight experience replay . In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017 , December 4-9, 2017, Long Beach, CA, USA,, Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett (Eds.). 5048--5058. Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, OpenAI Pieter Abbeel, and Wojciech Zaremba. 2017. Hindsight experience replay. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA,, Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett (Eds.). 5048--5058.

2. Xueying Bai , Jian Guan , and Hongning Wang . 2019. A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation . In Advances in Neural Information Processing Systems, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc , E. Fox, and R. Garnett (Eds.), Vol. 32 . Curran Associates, Inc. , 10735--10746. https://proceedings.neurips.cc/paper/ 2019 /file/e49eb6523da9e1c347bc148ea8ac55d3-Paper.pdf Xueying Bai, Jian Guan, and Hongning Wang. 2019. A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation. In Advances in Neural Information Processing Systems, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, and R. Garnett (Eds.), Vol. 32. Curran Associates, Inc., 10735--10746. https://proceedings.neurips.cc/paper/2019/file/e49eb6523da9e1c347bc148ea8ac55d3-Paper.pdf

3. Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient

4. Stabilizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation

5. Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation

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