Projects
Reading
People
Chat
SU\G
(đ¸)
/K¡U
Projects
Reading
People
Chat
Sign Up
Light
Dark
System
Scalable Neural Contextual Bandit for Recommender Systems
Zheqing Zhu
,
Benjamin Van Roy
Type:
Article
Publication Date:
2023-10-21
Citations:
1
DOI:
https://doi.org/10.1145/3583780.3615048
Share
Locations
arXiv (Cornell University) -
View
-
PDF
Similar Works
Action
Title
Year
Authors
+
Scalable Neural Contextual Bandit for Recommender Systems
2023
Zheqing Zhu
Benjamin Van Roy
+
Neural Contextual Bandits for Personalized Recommendation
2024
Yikun Ban
Yunzhe Qi
Jingrui He
+
Neural Contextual Bandits for Personalized Recommendation
2023
Yikun Ban
Yunzhe Qi
Jingrui He
+
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems
2022
Hao Wang
Yifei Ma
Hao Ding
Yuyang Wang
+
PDF
Chat
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems
2022
Hao Wang
Yifei Ma
Hao Ding
Yuyang Wang
+
PDF
Chat
Uncertainty of Joint Neural Contextual Bandit
2024
Hongbo Guo
Zheqing Zhu
+
Hierarchical Exploration for Accelerating Contextual Bandits
2012
Yisong Yue
Sue Ann Hong
Carlos Guestrin
+
Neural Collaborative Filtering Bandits via Meta Learning
2022
Yikun Ban
Yunzhe Qi
Tianxin Wei
Jingrui He
+
PDF
Chat
Contextual Bandit with Herding Effects: Algorithms and Recommendation Applications
2024
Luyue Xu
Liming Wang
Hong Xie
Mingqiang Zhou
+
Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Sampling
2023
Zheqing Zhu
Yueyang Liu
Kuang Xu
Benjamin Van Roy
+
Two-Stage Neural Contextual Bandits for Personalised News Recommendation
2022
Mengyan Zhang
Thanh Nguyen-Tang
Fangzhao Wu
Zhenyu He
Xing Xie
Cheng Soon Ong
+
A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation.
2021
Le Wu
Xiangnan He
Xiang Wang
Kun Zhang
Meng Wang
+
Conversational Contextual Bandit: Algorithm and Application
2019
Xiaoying Zhang
Hong Xie
Hang Li
John C. S. Lui
+
PDF
Chat
Conversational Contextual Bandit: Algorithm and Application
2020
Xiaoying Zhang
Hong Xie
Hang Li
John C. S. Lui
+
Toward Building Conversational Recommender Systems: A Contextual Bandit Approach
2019
Xiaoying Zhang
Hong Xie
Hang Li
John C. S. Lui
+
Epsilon non-Greedy: A Bandit Approach for Unbiased Recommendation via Uniform Data
2023
Sara Mirahmadi Sani
Seyed Abbas Hosseini
Hamid R. Rabiee
+
PDF
Chat
Epsilon non-Greedy: A Bandit Approach for Unbiased Recommendation via Uniform Data
2023
Sara Mirahmadi Sani
Seyed Abbas Hosseini
Hamid R. Rabiee
+
PDF
Chat
Neural Combinatorial Clustered Bandits for Recommendation Systems
2024
Baran Atalar
Carlee JoeâWong
+
PDF
Chat
Meta Clustering of Neural Bandits
2024
Yikun Ban
Yunzhe Qi
Tianxin Wei
Lihui Liu
Jingrui He
+
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
2022
Le Wu
Xiangnan He
Xiang Wang
Kun Zhang
Meng Wang
Works That Cite This (0)
Action
Title
Year
Authors
Works Cited by This (13)
Action
Title
Year
Authors
+
ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES
1933
W. R THOMPSON
+
PDF
Chat
A contextual-bandit approach to personalized news article recommendation
2010
Lihong Li
Wei Chu
John Langford
Robert E. Schapire
+
PDF
Chat
Learning to Optimize via Posterior Sampling
2014
Daniel Russo
Benjamin Van Roy
+
Wide & Deep Learning for Recommender Systems
2016
Heng-Tze Cheng
Levent Koç
Jeremiah Harmsen
Tal Shaked
Tushar Chandra
Hrishi Aradhye
Glen Anderson
Greg S. Corrado
Wei Koong Chai
Mustafa Ispir
+
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
2017
Huifeng Guo
Ruiming Tang
Yunming Ye
Zhenguo Li
Xiuqiang He
+
Neural Collaborative Filtering
2017
Xiangnan He
Lizi Liao
Hanwang Zhang
Liqiang Nie
Xia Hu
TatâSeng Chua
+
Linear Thompson sampling revisited
2017
Marc Abeille
Alessandro Lazaric
+
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations
2020
Dalin Guo
Sofia Ira Ktena
Pranay Kumar Myana
Ferenc HuszĂĄr
Wenzhe Shi
Alykhan Tejani
Michael Kneier
Sourav Das
+
PDF
Chat
Degenerate Feedback Loops in Recommender Systems
2019
Ray Jiang
Silvia Chiappa
Tor Lattimore
AndrĂĄs GyĂśrgy
Pushmeet Kohli
+
PDF
Chat
A Tutorial on Thompson Sampling
2018
Daniel Russo
Benjamin Van Roy
Abbas Kazerouni
Ian Osband
Zheng Wen