Deep Bayesian Bandits: Exploring in Online Personalized Recommendations

Deep Bayesian Bandits: Exploring in Online Personalized Recommendations

3 August 2020

Pranay K. Myana

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

9 / 9 papers shown

Title
Reinforcement Learning and Bandits for Speech and Language Processing: Tutorial, Review and Outlook Baihan Lin OffRL AI4TS 28 27 0 24 Oct 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 34 4 0 31 Jan 2022
Top-K Ranking Deep Contextual Bandits for Information Selection Systems Jade Freeman Michael Rawson 24 2 0 28 Jan 2022
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 273 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015