Deep Bayesian Bandits: Exploring in Online Personalized Recommendations

3 August 2020

Papers citing "Deep Bayesian Bandits: Exploring in Online Personalized Recommendations"

22 / 22 papers shown

Title
Transforming Location Retrieval at Airbnb: A Journey from Heuristics to Reinforcement Learning Dillon Davis Huiji Gao Weiwei Guo Thomas Legrand Malay Haldar Alex Deng Han Zhao Liwei He Sanjeev Katariya 32 0 0 23 Aug 2024
Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits Ziyi Huang Henry Lam Haofeng Zhang 33 0 0 20 Jun 2024
Uncertainty of Joint Neural Contextual Bandit Hongbo Guo Zheqing Zhu 37 0 0 04 Jun 2024
Epsilon non-Greedy: A Bandit Approach for Unbiased Recommendation via Uniform Data S.M.F. Sani Seyed Abbas Hosseini Hamid R. Rabiee OffRL 24 1 0 07 Oct 2023
Diversify and Conquer: Bandits and Diversity for an Enhanced E-commerce Homepage Experience Sangeet Jaiswal Korah T Malayil Saif Jawaid Sreekanth Vempati 21 0 0 25 Sep 2023
Interactive Graph Convolutional Filtering Jin Zhang Defu Lian Hong Xie Yawen Li Enhong Chen 27 0 0 04 Sep 2023
Scalable Neural Contextual Bandit for Recommender Systems Zheqing Zhu Benjamin Van Roy OffRL 24 9 0 26 Jun 2023
Reinforcement Learning and Bandits for Speech and Language Processing: Tutorial, Review and Outlook Baihan Lin OffRL AI4TS 28 27 0 24 Oct 2022
Two-Stage Neural Contextual Bandits for Personalised News Recommendation Mengyan Zhang Thanh Nguyen-Tang Fangzhao Wu Zhenyu He Xing Xie Cheng Soon Ong 19 4 0 26 Jun 2022
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network Yun-Da Tsai Shou-De Lin 38 5 0 17 Feb 2022
Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations A. A. Kocherzhenko Nirmal Sobha Kartha Tengfei Li Hsin-Yi Shih Shih Marco Mandic Mike Fuller Arshak Navruzyan 26 0 0 31 Jan 2022
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework Ziyi Huang H. Lam A. Meisami Haofeng Zhang 36 4 0 31 Jan 2022
Top-K Ranking Deep Contextual Bandits for Information Selection Systems Jade Freeman Michael Rawson 29 2 0 28 Jan 2022
Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction Kailun Wu Zhangming Chan Weijie Bian Lejian Ren Shiming Xiang Shuguang Han Hongbo Deng Bo Zheng 16 12 0 21 Dec 2021
Efficient Online Bayesian Inference for Neural Bandits Gerardo Duran-Martín Aleyna Kara Kevin Patrick Murphy BDL 19 13 0 01 Dec 2021
Deep Upper Confidence Bound Algorithm for Contextual Bandit Ranking of Information Selection Michael Rawson Jade Freeman 14 3 0 08 Oct 2021
Online Learning for Recommendations at Grubhub A. Egg OffRL OnRL 29 9 0 15 Jul 2021
Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling Simen Eide David S. Leslie A. Frigessi BDL OffRL 19 9 0 30 Apr 2021
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning Chao Du Zhifeng Gao Shuo Yuan Lining Gao Z. Li Yifan Zeng Xiaoqiang Zhu Jian Xu Kun Gai Kuang-chih Lee 25 18 0 25 Nov 2020
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility A. Chaney Brandon M Stewart Barbara E. Engelhardt CML 169 313 0 30 Oct 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015