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This paper studies an online selection problem, where a seller seeks to sequentially sell multiple copies of an item to arriving buyers. We consider an adversarial setting, making no modeling assumptions about buyers' valuations for the…

Computer Science and Game Theory · Computer Science 2024-10-11 Bo Sun , Hossein Nekouyan Jazi , Xiaoqi Tan , Raouf Boutaba

We consider the fundamental scenario where a single item is to be sold to one of two agents. Both agents draw their valuation for the item from the same probability distribution. However, only one of them submits a bid to the mechanism. The…

Computer Science and Game Theory · Computer Science 2025-08-26 Ioannis Caragiannis , Georgios Kalantzis

We study the optimal asset allocation problem for a fund manager whose compensation depends on the performance of her portfolio with respect to a benchmark. The objective of the manager is to maximise the expected utility of her final…

Portfolio Management · Quantitative Finance 2020-11-17 Flavio Angelini , Katia Colaneri , Stefano Herzel , Marco Nicolosi

A sequence of recent studies show that even in the simple setting of a single seller and a single buyer with additive, independent valuations over $m$ items, the revenue-maximizing mechanism is prohibitively complex. This problem has been…

Computer Science and Game Theory · Computer Science 2018-01-10 Michal Feldman , Ophir Friedler , Aviad Rubinstein

We provide sufficient conditions for revenue maximization in a two-good monopoly where the buyer's values for the items come from independent (but not necessarily identical) distributions over bounded intervals. Under certain distributional…

Computer Science and Game Theory · Computer Science 2015-11-24 Yiannis Giannakopoulos , Elias Koutsoupias

We study computational questions in a game-theoretic model that, in particular, aims to capture advertising/persuasion applications such as viral marketing. Specifically, we consider a multi-agent Bayesian persuasion model where an informed…

Computer Science and Game Theory · Computer Science 2016-03-07 Yakov Babichenko , Siddharth Barman

We consider price competition among multiple sellers over a selling horizon of $T$ periods. In each period, sellers simultaneously offer their prices (which are made public) and subsequently observe their respective demand (not made…

Machine Learning · Statistics 2026-05-08 Daniele Bracale , Moulinath Banerjee , Cong Shi , Yuekai Sun

We study the problem of a seller dynamically pricing $d$ distinct types of indivisible goods, when faced with the online arrival of unit-demand buyers drawn independently from an unknown distribution. The goods are not in limited supply,…

Data Structures and Algorithms · Computer Science 2017-06-13 Aaron Roth , Aleksandrs Slivkins , Jonathan Ullman , Zhiwei Steven Wu

A seller posts a price for a single object. The seller's and buyer's values may be interdependent. We characterize the set of payoff vectors across all information structures. Simple feasibility and individual-rationality constraints…

Theoretical Economics · Economics 2025-09-10 Navin Kartik , Weijie Zhong

Online platforms collect rich information about participants and then share some of this information back with them to improve market outcomes. In this paper we study the following information disclosure problem in two-sided markets: If a…

Theoretical Economics · Economics 2023-09-01 Bar Light , Ramesh Johari , Gabriel Weintraub

We study multi-product monopoly pricing where the seller jointly designs the selling mechanism and the information structure for the buyer to learn his values. Unlike the case with exogenous information, we show that when the seller…

Computer Science and Game Theory · Computer Science 2025-10-29 Yang Cai , Yingkai Li , Jinzhao Wu

Lately, personalized marketing has become important for retail/e-retail firms due to significant rise in online shopping and market competition. Increase in online shopping and high market competition has led to an increase in promotional…

Machine Learning · Computer Science 2020-10-19 Ankur Verma

Diverse keyword suggestions for a given landing page or matching queries to diverse documents is an active research area in online advertising. Modern search engines provide advertisers with products like Dynamic Search Ads and Smart…

Information Retrieval · Computer Science 2020-12-02 Shreya Malani , Dinesh Gaurav , Anoop Vallabhajosyula , Rahul Agrawal

We consider the revenue maximization problem for an online retailer who plans to display in order a set of products differing in their prices and qualities. Consumers have attention spans, i.e., the maximum number of products they are…

Machine Learning · Computer Science 2025-11-11 Ningyuan Chen , Anran Li , Shuoguang Yang

The fast growth of communication technology within the concept of smart grids can provide data and control signals from/to all consumers in an online fashion. This could foster more participation for end-user customers. These types of…

Systems and Control · Electrical Eng. & Systems 2020-09-11 Arman Alahyari , David Pozo

We consider the problem of an auctioneer who faces the task of selling a good (drawn from a known distribution) to a set of buyers, when the auctioneer does not have the capacity to describe to the buyers the exact identity of the good that…

Computer Science and Game Theory · Computer Science 2014-01-08 Shaddin Dughmi , Nicole Immorlica , Aaron Roth

We study the optimal usage-based pricing problem in a resource-constrained network with one profit-maximizing service provider and multiple groups of surplus-maximizing users. With the assumption that the service provider knows the utility…

Networking and Internet Architecture · Computer Science 2015-03-17 Shuqin Li , Jianwei Huang

Motivated by online retail, we consider the problem of selling one item (e.g., an ad slot) to two non-excludable buyers (say, a merchant and a brand). This problem captures, for example, situations where a merchant and a brand cooperatively…

Computer Science and Game Theory · Computer Science 2025-05-26 Gagan Aggarwal , Ashwinkumar Badanidiyuru , Paul Dütting , Federico Fusco

In many real world problems, optimization decisions have to be made with limited information. The decision maker may have no a priori or posteriori data about the often nonconvex objective function except from on a limited number of points…

Optimization and Control · Mathematics 2011-11-10 Tansu Alpcan

We consider joint optimization and learning problems arising in real-time decision systems. While most existing work focuses primarily on convex, revenue-based objectives, we extend this line of research to multi-objective formulations. In…

Optimization and Control · Mathematics 2026-04-14 Zijun Li , Aswin Kannan