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We study the budget allocation problem in online marketing campaigns that utilize previously collected offline data. We first discuss the long-term effect of optimizing marketing budget allocation decisions in the offline setting. To…

Machine Learning · Computer Science 2023-09-07 Tianchi Cai , Jiyan Jiang , Wenpeng Zhang , Shiji Zhou , Xierui Song , Li Yu , Lihong Gu , Xiaodong Zeng , Jinjie Gu , Guannan Zhang

Co-branding has become a vital strategy for businesses aiming to expand market reach within recommendation systems. However, identifying effective cross-industry partnerships remains challenging due to resource imbalances, uncertain brand…

Machine Learning · Computer Science 2025-05-29 Xiangxiang Dai , Xiaowei Sun , Jinhang Zuo , Xutong Liu , John C. S. Lui

Advertisers usually enjoy the flexibility to choose criteria like target audience, geographic area and bid price when planning an campaign for online display advertising, while they lack forecast information on campaign performance to…

Machine Learning · Computer Science 2022-02-25 Jun Chen , Cheng Chen , Huayue Zhang , Qing Tan

This paper concerns the mechanism design for online resource allocation in a strategic setting. In this setting, a single supplier allocates capacity-limited resources to requests that arrive in a sequential and arbitrary manner. Each…

Computer Science and Game Theory · Computer Science 2023-10-10 Xiaoqi Tan , Bo Sun , Alberto Leon-Garcia , Yuan Wu , Danny H. K. Tsang

Marketing optimization, commonly formulated as an online budget allocation problem, has emerged as a pivotal factor in driving user growth. Most existing research addresses this problem by following the principle of 'first predict then…

Machine Learning · Computer Science 2025-06-03 Xiaohan Wang , Yu Zhang , Guibin Jiang , Bing Cheng , Wei Lin

We study a general problem of allocating limited resources to heterogeneous customers over time under model uncertainty. Each type of customer can be serviced using different actions, each of which stochastically consumes some combination…

Artificial Intelligence · Computer Science 2021-08-31 Wang Chi Cheung , Will Ma , David Simchi-Levi , Xinshang Wang

Today's top advertisers typically manage hundreds of campaigns simultaneously and consistently launch new ones throughout the year. A crucial challenge for marketing managers is determining the optimal allocation of limited budgets across…

Machine Learning · Statistics 2024-09-04 Lin Ge , Yang Xu , Jianing Chu , David Cramer , Fuhong Li , Kelly Paulson , Rui Song

Online platforms often incentivize consumers to improve user engagement and platform revenue. Since different consumers might respond differently to incentives, individual-level budget allocation is an essential task in marketing campaigns.…

Machine Learning · Computer Science 2023-02-10 Ziang Yan , Shusen Wang , Guorui Zhou , Jingjian Lin , Peng Jiang

A central problem in business concerns the optimal allocation of limited resources to a set of available tasks, where the payoff of these tasks is inherently uncertain. In credit card fraud detection, for instance, a bank can only assign a…

Machine Learning · Computer Science 2022-02-10 Toon Vanderschueren , Bart Baesens , Tim Verdonck , Wouter Verbeke

In online advertising, the inherent complexity and dynamic nature of advertising environments necessitate the use of auto-bidding services to assist advertisers in bid optimization. This complexity is further compounded in multi-channel…

Artificial Intelligence · Computer Science 2026-02-27 Xinxin Yang , Yangyang Tang , Yikun Zhou , Yaolei Liu , Yun Li , Bo Yang

The majority of online marketplaces offer promotion programs to sellers to acquire additional customers for their products. These programs typically allow sellers to allocate advertising budgets to promote their products, with higher…

Computer Science and Game Theory · Computer Science 2025-02-05 Anastasiia Soboleva , Alexander Ledovsky , Yuriy Dorn , Egor Samosvat , Andrey Tikhanov , Fyodor Prazdnikov

Online Resource Allocation addresses the problem of efficiently allocating limited resources to buyers with incomplete knowledge of future requests. In our setting, buyers arrive sequentially requesting a set of items, each with a value…

Computer Science and Game Theory · Computer Science 2026-02-11 Dimitris Fotakis , Charalampos Platanos , Thanos Tolias

Complex urban road networks with high vehicle occupancy frequently face severe traffic congestion. Designing an effective strategy for managing multiple traffic lights plays a crucial role in managing congestion. However, most current…

Machine Learning · Computer Science 2024-08-15 Taeyoung Yun , Kanghoon Lee , Sujin Yun , Ilmyung Kim , Won-Woo Jung , Min-Cheol Kwon , Kyujin Choi , Yoohyeon Lee , Jinkyoo Park

Online advertising in E-commerce platforms provides sellers an opportunity to achieve potential audiences with different target goals. Ad serving systems (like display and search advertising systems) that assign ads to pages should satisfy…

Machine Learning · Computer Science 2019-10-09 Chao Wei , Weiru Zhang , Shengjie Sun , Fei Li , Xiaonan Meng , Yi Hu , Hao Wang

In online advertising (Ad), advertisers are always eager to know how to globally optimize their budget allocation strategies across different channels for more conversions such as orders, payments, etc. Ignoring competition among different…

Computer Science and Game Theory · Computer Science 2023-05-12 Guangyuan Shen , Shenjie Sun , Dehong Gao , Shaolei Li , Libin Yang , Yongping Shi , Wei Ning

Motivated by Internet advertising applications, online allocation problems have been studied extensively in various adversarial and stochastic models. While the adversarial arrival models are too pessimistic, many of the stochastic (such as…

Data Structures and Algorithms · Computer Science 2017-11-17 Hossein Esfandiari , Nitish Korula , Vahab Mirrokni

High-quality machine learning models are dependent on access to high-quality training data. When the data are not already available, it is tedious and costly to obtain them. Data markets help with identifying valuable training data: model…

Machine Learning · Computer Science 2023-06-06 Boxin Zhao , Boxiang Lyu , Raul Castro Fernandez , Mladen Kolar

We study an online learning problem on dynamic pricing and resource allocation, where we make joint pricing and inventory decisions to maximize the overall net profit. We consider the stochastic dependence of demands on the price, which…

Machine Learning · Computer Science 2025-05-23 Jianyu Xu , Xuan Wang , Yu-Xiang Wang , Jiashuo Jiang

Sequential incentive marketing is an important approach for online businesses to acquire customers, increase loyalty and boost sales. How to effectively allocate the incentives so as to maximize the return (e.g., business objectives) under…

Artificial Intelligence · Computer Science 2023-03-03 Shuai Xiao , Le Guo , Zaifan Jiang , Lei Lv , Yuanbo Chen , Jun Zhu , Shuang Yang

Effective budget allocation is crucial for optimizing the performance of digital advertising campaigns. However, the development of practical budget allocation algorithms remain limited, primarily due to the lack of public datasets and…

Machine Learning · Computer Science 2025-02-06 Briti Gangopadhyay , Zhao Wang , Alberto Silvio Chiappa , Shingo Takamatsu
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