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Online retailers often use third-party demand-side-platforms (DSPs) to conduct offsite advertising and reach shoppers across the Internet on behalf of their advertisers. The process involves the retailer participating in instant auctions…

Systems and Control · Electrical Eng. & Systems 2023-10-26 Hangjian Li , Dong Xu , Konstantin Shmakov , Kuang-Chih Lee , Wei Shen

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

In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform revenue. However, most of the state-of-the-art auction…

Computer Science and Game Theory · Computer Science 2021-01-11 Zhilin Zhang , Xiangyu Liu , Zhenzhe Zheng , Chenrui Zhang , Miao Xu , Junwei Pan , Chuan Yu , Fan Wu , Jian Xu , Kun Gai

In targeted online advertising, advertisers look for maximizing campaign performance under delivery constraint within budget schedule. Most of the advertisers typically prefer to impose the delivery constraint to spend budget smoothly over…

Artificial Intelligence · Computer Science 2015-06-22 Jian Xu , Kuang-chih Lee , Wentong Li , Hang Qi , Quan Lu

Since 2019, most ad exchanges and sell-side platforms (SSPs), in the online advertising industry, shifted from second to first price auctions. Due to the fundamental difference between these auctions, demand-side platforms (DSPs) have had…

Real-Time Bidding (RTB) is an important paradigm in display advertising, where advertisers utilize extended information and algorithms served by Demand Side Platforms (DSPs) to improve advertising performance. A common problem for DSPs is…

Computer Science and Game Theory · Computer Science 2019-05-30 Xun Yang , Yasong Li , Hao Wang , Di Wu , Qing Tan , Jian Xu , Kun Gai

We study the problem of an online advertising system that wants to optimally spend an advertiser's given budget for a campaign across multiple platforms, without knowing the value for showing an ad to the users on those platforms. We model…

Computer Science and Game Theory · Computer Science 2021-03-26 Vashist Avadhanula , Riccardo Colini-Baldeschi , Stefano Leonardi , Karthik Abinav Sankararaman , Okke Schrijvers

Many machine learning models, such as logistic regression~(LR) and support vector machine~(SVM), can be formulated as composite optimization problems. Recently, many distributed stochastic optimization~(DSO) methods have been proposed to…

Machine Learning · Statistics 2016-12-13 Shen-Yi Zhao , Ru Xiang , Ying-Hao Shi , Peng Gao , Wu-Jun Li

In sponsored search advertising, keywords serve as an essential bridge linking advertisers, search users and search engines. Advertisers have to deal with a series of keyword decisions throughout the entire lifecycle of search advertising…

Information Retrieval · Computer Science 2022-03-01 Yanwu Yang , Bernard J. Jansen , Yinghui Yang , Xunhua Guo , Daniel Zeng

Demand Side Response (DSR) is a strategy that enables consumers to actively participate in managing electricity demand. It aims to alleviate strain on the grid during high demand and promote a more balanced and efficient use of (renewable)…

Real-time bidding (RTB) based display advertising has become one of the key technological advances in computational advertising. RTB enables advertisers to buy individual ad impressions via an auction in real-time and facilitates the…

Computer Science and Game Theory · Computer Science 2018-03-13 Kan Ren , Weinan Zhang , Ke Chang , Yifei Rong , Yong Yu , Jun Wang

Sponsored search positions are typically allocated through real-time auctions, where the outcomes depend on advertisers' quality-adjusted bids - the product of their bids and quality scores. Although quality scoring helps promote ads with…

Computer Science and Game Theory · Computer Science 2025-09-01 Mohammad Rashid , Omid Rafieian , Soheil Ghili

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

Over the last decade, digital media (web or app publishers) generalized the use of real time ad auctions to sell their ad spaces. Multiple auction platforms, also called Supply-Side Platforms (SSP), were created. Because of this…

In programmatic advertising, ad slots are usually sold using second-price (SP) auctions in real-time. The highest bidding advertiser wins but pays only the second-highest bid (known as the winning price). In SP, for a single item, the…

Machine Learning · Computer Science 2020-01-22 Aritra Ghosh , Saayan Mitra , Somdeb Sarkhel , Jason Xie , Gang Wu , Viswanathan Swaminathan

We present a data-driven algorithm that advertisers can use to automate their digital ad-campaigns at online publishers. The algorithm enables the advertiser to search across available target audiences and ad-media to find the best possible…

Machine Learning · Computer Science 2022-09-20 Wenjia Ba , J. Michael Harrison , Harikesh S. Nair

Despite their remarkable success in complex tasks propelling widespread adoption, large language-model-based agents still face critical deployment challenges due to prohibitive latency and inference costs. While recent work has explored…

Artificial Intelligence · Computer Science 2025-09-23 Yilin Guan , Qingfeng Lan , Sun Fei , Dujian Ding , Devang Acharya , Chi Wang , William Yang Wang , Wenyue Hua

Industrial sponsored search system (SSS) can be logically divided into three modules: keywords matching, ad retrieving, and ranking. During ad retrieving, the ad candidates grow exponentially. A query with high commercial value might…

Bid optimization in online advertising relies on black-box machine-learning models that learn bidding decisions from historical data. However, these approaches fail to replicate human experts' adaptive, experience-driven, and globally…

Artificial Intelligence · Computer Science 2026-03-06 Huixiang Luo , Longyu Gao , Yaqi Liu , Qianqian Chen , Pingchun Huang , Tianning Li

Guaranteed display advertising is crucial for platform monetization, yet existing methods often operate under a single-slot assumption, limiting their ability to optimize allocation across multi-slot page views. In this paper, we propose a…

Machine Learning · Computer Science 2026-05-22 Zhaoqi Zhang , Jiaming Deng , Miao Xie , Linyou Cai , Qianlong Xie , Xingxing Wang , Siqiang Luo , Gao Cong
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