Counterfactual Multi-player Bandits for Explainable Recommendation Diversification

Counterfactual Multi-player Bandits for Explainable Recommendation Diversification

27 May 2025

Papers citing "Counterfactual Multi-player Bandits for Explainable Recommendation Diversification"

16 / 16 papers shown

Title
Shapley Value-driven Data Pruning for Recommender Systems Yansen Zhang Xiaokun Zhang Ziqiang Cui Chen Ma TDI 46 0 0 28 May 2025
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning Dusan Stamenkovic Alexandros Karatzoglou Ioannis Arapakis Xin Xin Kleomenis Katevas 34 48 0 28 Oct 2021
Counterfactual Explainable Recommendation Juntao Tan Shuyuan Xu Yingqiang Ge Yunqi Li Xu Chen Yongfeng Zhang CML 46 143 0 24 Aug 2021
Sliding Spectrum Decomposition for Diversified Recommendation Yanhua Huang Weikun Wang Lei Zhang Ruiwen Xu 24 41 0 12 Jul 2021
A Hybrid Bandit Framework for Diversified Recommendation Qinxu Ding Yong Liu Chunyan Miao Feixue Cheng Haihong Tang 18 24 0 24 Dec 2020
Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions Sébastien Bubeck Thomas Budzinski Mark Sellke 13 18 0 08 Nov 2020
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation Xiangnan He Kuan Deng Xiang Wang Yan Li Yongdong Zhang Meng Wang GNN 107 3,586 0 06 Feb 2020
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems Azin Ghazimatin Oana Balalau Rishiraj Saha Roy Gerhard Weikum FAtt 36 99 0 19 Nov 2019
Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control Mo Yu Shiyu Chang Yang Zhang Tommi Jaakkola 101 143 0 29 Oct 2019
Introduction to Multi-Armed Bandits Aleksandrs Slivkins 199 999 0 15 Apr 2019
Explainable Recommendation: A Survey and New Perspectives Yongfeng Zhang Xu Chen XAI LRM 67 870 0 30 Apr 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 48 2,332 0 01 Nov 2017
Wide & Deep Learning for Recommender Systems Heng-Tze Cheng L. Koc Jeremiah Harmsen T. Shaked Tushar Chandra ... Zakaria Haque Lichan Hong Vihan Jain Xiaobing Liu Hemal Shah HAI VLM 124 3,636 0 24 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 392 16,765 0 16 Feb 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 519 149,474 0 22 Dec 2014
A Contextual-Bandit Approach to Personalized News Article Recommendation Lihong Li Wei Chu John Langford Robert Schapire 219 2,935 0 28 Feb 2010