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The growth in the use of online advertising to foster brand awareness over recent years is largely attributable to the ubiquity of social media. One pivotal technology contributing to the success of online brand advertising is frequency…

Computer Science and Game Theory · Computer Science 2025-01-10 Yuan Gao , Mu Qiao

Constrained $k$-submodular maximization is a general framework that captures many discrete optimization problems such as ad allocation, influence maximization, personalized recommendation, and many others. In many of these applications,…

Data Structures and Algorithms · Computer Science 2023-05-26 Fabian Spaeh , Alina Ene , Huy L. Nguyen

We introduce and study a general version of the fractional online knapsack problem with multiple knapsacks, heterogeneous constraints on which items can be assigned to which knapsack, and rate-limiting constraints on the assignment of items…

Data Structures and Algorithms · Computer Science 2020-10-20 Bo Sun , Ali Zeynali , Tongxin Li , Mohammad Hajiesmaili , Adam Wierman , Danny H. K. Tsang

Live online social broadcasting services like YouTube Live and Twitch have steadily gained popularity due to improved bandwidth, ease of generating content and the ability to earn revenue on the generated content. In contrast to traditional…

Social and Information Networks · Computer Science 2016-11-02 Vikram Krishnamurthy , Anup Aprem , Sujay Bhatt

In many online advertisement (ad) exchanges, ad slots are each sold via a separate second-price auction. This paper considers the bidder's problem of maximizing the value of ads they purchase in these auctions, subject to budget…

Computer Science and Game Theory · Computer Science 2020-03-16 Jonathan Amar , Nicholas Renegar

Semi-online algorithms that are allowed to perform a bounded amount of repacking achieve guaranteed good worst-case behaviour in a more realistic setting. Most of the previous works focused on minimization problems that aim to minimize some…

Data Structures and Algorithms · Computer Science 2021-04-21 Sebastian Berndt , Kilian Grage , Klaus Jansen , Lukas Johannsen , Maria Kosche

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

Internet search companies sell advertisement slots based on users' search queries via an auction. While there has been a lot of attention on the auction process and its game-theoretic aspects, our focus is on the advertisers. In particular,…

Data Structures and Algorithms · Computer Science 2007-05-23 Jon Feldman , S. Muthukrishnan , Martin Pal , Cliff Stein

Numerous combinatorial optimization problems (knapsack, maximum-weight matching, etc.) can be expressed as \emph{subset maximization problems}: One is given a ground set $N=\{1,\dots,n\}$, a collection $\mathcal{F}\subseteq 2^N$ of subsets…

Data Structures and Algorithms · Computer Science 2019-05-13 Evripidis Bampis , Bruno Escoffier , Kevin Schewior , Alexandre Teiller

We consider an online version of the well-studied network utility maximization problem, where users arrive one by one and an operator makes irrevocable decisions for each user without knowing the details of future arrivals. We propose a…

Data Structures and Algorithms · Computer Science 2021-01-27 Ying Cao , Bo Sun , Danny H. K. Tsang

We analyze the problem of how to optimally bid for ad spaces in online ad auctions. For this we consider the general case of multiple ad campaigns with overlapping targeting criteria. In our analysis we first characterize the structure of…

Optimization and Control · Mathematics 2020-04-16 Erik Tillberg , Peter Marbach , Ravi Mazumdar

This paper studies online optimization under inventory (budget) constraints. While online optimization is a well-studied topic, versions with inventory constraints have proven difficult. We consider a formulation of inventory-constrained…

Performance · Computer Science 2024-12-20 Qiulin Lin , Hanling Yi , John Pang , Minghua Chen , Adam Wierman , Michael Honig , Yuanzhang Xiao

Pay-per-click advertising includes various formats (\emph{e.g.}, search, contextual, social) with a total investment of more than 200 billion USD per year worldwide. An advertiser is given a daily budget to allocate over several, even…

Machine Learning · Computer Science 2020-03-04 Alessandro Nuara , Francesco Trovò , Nicola Gatti , Marcello Restelli

Online social network has been one of the most important platforms for viral marketing. Most of existing researches about diffusion of adoptions of new products on networks are about one diffusion. That is, only one piece of information…

Social and Information Networks · Computer Science 2023-05-17 Tiantian Chen , Jianxiong Guo , Weili Wu

Uplift models support decision-making in marketing campaign planning. Estimating the causal effect of a marketing treatment, an uplift model facilitates targeting communication to responsive customers and efficient allocation of marketing…

Machine Learning · Computer Science 2019-11-21 Robin M. Gubela , Stefan Lessmann , Szymon Jaroszewicz

In sponsored search advertising, advertisers need to make a series of keyword decisions. Among them, how to group these keywords to form several adgroups within a campaign is a challenging task, due to the highly uncertain environment of…

Artificial Intelligence · Computer Science 2022-03-07 Huiran Li , Yanwu Yang

We study in this paper a revenue management problem with add-on discounts. The problem is motivated by the practice in the video game industry, where a retailer offers discounts on selected supportive products (e.g. video games) to…

Data Structures and Algorithms · Computer Science 2020-05-05 David Simchi-Levi , Rui Sun , Huanan Zhang

Promotions and discounts have become key components of modern e-commerce platforms. For online travel platforms (OTPs), popular promotions include room upgrades, free meals and transportation services. By offering these promotions,…

Machine Learning · Computer Science 2020-09-29 Dmitri Goldenberg , Javier Albert , Lucas Bernardi , Pablo Estevez

A retailer is purchasing goods in bundles from suppliers and then selling these goods in bundles to customers; her goal is to maximize profit, which is the revenue obtained from selling goods minus the cost of purchasing those goods. In…

Data Structures and Algorithms · Computer Science 2025-08-01 Yossi Azar , Niv Buchbinder , Roie Levin , Or Vardi

In recent years, RTB(Real Time Bidding) becomes a popular online advertisement trading method. During the auction, each DSP(Demand Side Platform) is supposed to evaluate current opportunity and respond with an ad and corresponding bid…

Machine Learning · Statistics 2017-12-29 Huahui Liu , Mingrui Zhu , Xiaonan Meng , Yi Hu , Hao Wang