Dear: Deep reinforcement learning for online advertising impression in recommender systems

X Zhao, C Gu, H Zhang, X Yang, X Liu… - Proceedings of the AAAI …, 2021 - ojs.aaai.org
With the recent prevalence of Reinforcement Learning (RL), there have been tremendous
interests in utilizing RL for online advertising in recommendation platforms (eg, e-commerce …

" Deep reinforcement learning for search, recommendation, and online advertising: a survey" by **angyu Zhao, Long **a, Jiliang Tang, and Dawei Yin with Martin …

X Zhao, L **a, J Tang, D Yin - ACM sigweb newsletter, 2019 - dl.acm.org
Search, recommendation, and online advertising are the three most important information-
providing mechanisms on the web. These information seeking techniques, satisfying users' …

Breaking the traditional: a survey of algorithmic mechanism design applied to economic and complex environments

Q Chen, X Wang, ZL Jiang, Y Wu, H Li, L Cui… - Neural Computing and …, 2023 - Springer
The mechanism design theory can be applied not only in the economy but also in many
fields, such as politics and military affairs, which has important practical and strategic …

Sliding-window thompson sampling for non-stationary settings

F Trovo, S Paladino, M Restelli, N Gatti - Journal of Artificial Intelligence …, 2020 - jair.org
Abstract Multi-Armed Bandit (MAB) techniques have been successfully applied to many
classes of sequential decision problems in the past decades. However, non-stationary …

Jointly learning to recommend and advertise

X Zhao, X Zheng, X Yang, X Liu, J Tang - Proceedings of the 26th ACM …, 2020 - dl.acm.org
Online recommendation and advertising are two major income channels for online
recommendation platforms (eg e-commerce and news feed site). However, most platforms …

Online joint bid/daily budget optimization of internet advertising campaigns

A Nuara, F Trovò, N Gatti, M Restelli - Artificial Intelligence, 2022 - Elsevier
Pay-per-click advertising includes various formats (eg, search, contextual, social) with a total
investment of more than 200 billion USD per year worldwide. An advertiser is given a daily …

Deep reinforcement learning for information retrieval: Fundamentals and advances

W Zhang, X Zhao, L Zhao, D Yin, GH Yang… - Proceedings of the 43rd …, 2020 - dl.acm.org
Information retrieval (IR) techniques, such as search, recommendation and online
advertising, satisfying users' information needs by suggesting users personalized objects …

E-commerce promotions personalization via online multiple-choice knapsack with uplift modeling

J Albert, D Goldenberg - Proceedings of the 31st ACM International …, 2022 - dl.acm.org
Promotions and discounts are essential components of modern e-commerce platforms,
where they are often used to incentivize customers towards purchase completion …

Disentangling the impact of bidding price on advertising performance in E-commerce search advertising: The moderating role of product competitiveness

P Qiu, Z Cai, X Kong, HK Chan, Y Shi - Information & Management, 2025 - Elsevier
Though E-commerce search advertising has become an increasingly prevalent approach for
online retailers to promote their products, it is nontrivial for online retailers to use search …

Online learning of network bottlenecks via minimax paths

N Åkerblom, FS Hoseini, M Haghir Chehreghani - Machine Learning, 2023 - Springer
In this paper, we study bottleneck identification in networks via extracting minimax paths.
Many real-world networks have stochastic weights for which full knowledge is not available …