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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

We address the challenge of finding algorithms for online allocation (i.e. bipartite matching) using a machine learning approach. In this paper, we focus on the AdWords problem, which is a classical online budgeted matching problem of both…

Machine Learning · Computer Science 2020-10-19 Goran Zuzic , Di Wang , Aranyak Mehta , D. Sivakumar

Real-time bidding (RTB) has become a critical way of online advertising. In RTB, an advertiser can participate in bidding ad impressions to display its advertisements. The advertiser determines every impression's bidding price according to…

Machine Learning · Computer Science 2021-10-12 Mengjuan Liu , Jinyu Liu , Zhengning Hu , Yuchen Ge , Xuyun Nie

Graph data is ubiquitous in academia and industry, from social networks to bioinformatics. The pervasiveness of graphs today has raised the demand for algorithms that can answer various questions: Which products would a user like to…

Machine Learning · Computer Science 2020-12-01 Minji Yoon , Théophile Gervet , Bryan Hooi , Christos Faloutsos

We study a general online combinatorial auction problem in algorithmic mechanism design. A provider allocates multiple types of capacity-limited resources to customers that arrive in a sequential and arbitrary manner. Each customer has a…

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

Digital advertising is a critical part of many e-commerce platforms such as Taobao and Amazon. While in recent years a lot of attention has been drawn to the consumer side including canonical problems like ctr/cvr prediction, the advertiser…

Information Retrieval · Computer Science 2021-11-02 Zongtao Liu , Bin Ma , Quan Liu , Jian Xu , Bo Zheng

First-price auctions have very recently swept the online advertising industry, replacing second-price auctions as the predominant auction mechanism on many platforms. This shift has brought forth important challenges for a bidder: how…

Machine Learning · Computer Science 2025-09-26 Yanjun Han , Zhengyuan Zhou , Aaron Flores , Erik Ordentlich , Tsachy Weissman

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

Auction design for the modern advertising market has gained significant prominence in the field of game theory. With the recent rise of auto-bidding tools, an increasing number of advertisers in the market are utilizing these tools for…

Computer Science and Game Theory · Computer Science 2024-12-31 Changfeng Xu , Chao Peng , Chenyang Xu , Zhengfeng Yang

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

This note is a complementary material for the solution of optimal real-time bidding function in paper "Optimal Real-Time Bidding for Display Advertising, KDD 2014", where the estimated cost is taken as the bid price, i.e., the upper bound…

Computer Science and Game Theory · Computer Science 2016-02-03 Weinan Zhang , Kan Ren , Jun Wang

As a research community, we are still lacking a systematic understanding of the progress on adversarial robustness which often makes it hard to identify the most promising ideas in training robust models. A key challenge in benchmarking…

The rapid proliferation of machine learning models across domains and deployment settings has given rise to various communities (e.g. industry practitioners) which seek to benchmark models across tasks and objectives of personal value.…

Machine Learning · Computer Science 2021-11-09 Avanika Narayan , Piero Molino , Karan Goel , Willie Neiswanger , Christopher Ré

In the matroid buyback problem, an algorithm observes a sequence of bids and must decide whether to accept each bid at the moment it arrives, subject to a matroid constraint on the set of accepted bids. Decisions to reject bids are…

Computer Science and Game Theory · Computer Science 2009-11-30 Ashwinkumar B. V. , Robert Kleinberg

Sponsored search is an important monetization channel for search engines, in which an auction mechanism is used to select the ads shown to users and determine the prices charged from advertisers. There have been several pieces of work in…

Computer Science and Game Theory · Computer Science 2014-06-05 Di He , Wei Chen , Liwei Wang , Tie-Yan Liu

This paper develops algorithms to solve strong-substitutes product-mix auctions. That is, it finds competitive equilibrium prices and quantities for agents who use this auction's bidding language to truthfully express their…

Computer Science and Game Theory · Computer Science 2023-07-11 Elizabeth Baldwin , Paul W. Goldberg , Paul Klemperer , Edwin Lock

A typical real-time ad-serving funnel comprises ad targeting, conversion modeling (e.g., click-through rate prediction), budget pacing (bidding), and auction processes. While there is a wealth of research and articles on ad targeting and…

Computer Science and Game Theory · Computer Science 2025-03-11 Yuanlong Chen

In practice, most auction mechanisms are not strategy-proof, so equilibrium analysis is required to predict bidding behavior. In many auctions, though, an exact equilibrium is not known and one would like to understand whether -- manually…

Computer Science and Game Theory · Computer Science 2024-08-22 Fabian R. Pieroth , Tuomas Sandholm

The effectiveness of advertising in e-commerce largely depends on the ability of merchants to bid on and win impressions for their targeted users. The bidding procedure is highly complex due to various factors such as market competition,…

Information Retrieval · Computer Science 2023-12-29 Artem Betlei , Mariia Vladimirova , Mehdi Sebbar , Nicolas Urien , Thibaud Rahier , Benjamin Heymann

Path planning is an active area of research essential for many applications in robotics. Popular techniques include graph-based searches and sampling-based planners. These approaches are powerful but have limitations. This paper continues…

Robotics · Computer Science 2020-12-10 Marlin P. Strub , Jonathan D. Gammell
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