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Algorithmic decision-making in societal contexts, such as retail pricing, loan administration, recommendations on online platforms, etc., can be framed as stochastic optimization under bandit feedback, which typically requires…

Machine Learning · Computer Science 2024-10-22 Jad Salem , Swati Gupta , Vijay Kamble

The prevalence of e-commerce has made detailed customers' personal information readily accessible to retailers, and this information has been widely used in pricing decisions. When involving personalized information, how to protect the…

Cryptography and Security · Computer Science 2021-07-27 Xi Chen , David Simchi-Levi , Yining Wang

We investigate brokerage between traders from an online learning perspective. At any round $t$, two traders arrive with their private valuations, and the broker proposes a trading price. Unlike other bilateral trade problems already studied…

Machine Learning · Computer Science 2023-10-19 Nataša Bolić , Tommaso Cesari , Roberto Colomboni

We study repeated bilateral trade when the valuations of the sellers and the buyers are contextual. More precisely, the agents' valuations are given by the inner product of a context vector with two unknown $d$-dimensional vectors -- one…

Computer Science and Game Theory · Computer Science 2026-02-16 Romain Cosson , Federico Fusco , Anupam Gupta , Stefano Leonardi , Renato Paes Leme , Matteo Russo

Two-sided online matching platforms are employed in various markets. However, agents' preferences in the current market are usually implicit and unknown, thus needing to be learned from data. With the growing availability of dynamic side…

Machine Learning · Computer Science 2024-05-30 Yuantong Li , Chi-hua Wang , Guang Cheng , Will Wei Sun

In this paper, we investigate the online allocation problem of maximizing the overall revenue subject to both lower and upper bound constraints. Compared to the extensively studied online problems with only resource upper bounds, the…

Machine Learning · Computer Science 2023-01-31 Qixin Zhang , Wenbing Ye , Zaiyi Chen , Haoyuan Hu , Enhong Chen , Yang Yu

Our society can benefit immensely from algorithmic decision-making and similar types of artificial intelligence. But algorithmic decision-making can also have discriminatory effects. This paper examines that problem, using online price…

Computers and Society · Computer Science 2025-09-30 Frederik Zuiderveen Borgesius

We study the online multi-class selection problem with group fairness guarantees, where limited resources must be allocated to sequentially arriving agents. Our work addresses two key limitations in the existing literature. First, we…

Machine Learning · Computer Science 2025-10-27 Faraz Zargari , Hossein Nekouyan , Lyndon Hallett , Bo Sun , Xiaoqi Tan

Systematic discriminatory biases present in our society influence the way data is collected and stored, the way variables are defined, and the way scientific findings are put into practice as policy. Automated decision procedures and…

Machine Learning · Computer Science 2019-05-29 Razieh Nabi , Daniel Malinsky , Ilya Shpitser

We study the problem of fairly allocating indivisible goods to agents in an online setting, where goods arrive sequentially and must be allocated irrevocably. Focusing on the popular fairness notions of envy-freeness, proportionality, and…

Computer Science and Game Theory · Computer Science 2026-05-29 Tzeh Yuan Neoh , Jannik Peters , Nicholas Teh

We consider dynamic pricing algorithms as applied to the online set cover problem. In the dynamic pricing framework, we assume the standard client server model with the additional constraint that the server can only place prices over the…

Data Structures and Algorithms · Computer Science 2024-09-24 Max Bender , Aum Desai , Jialin He , Oliver Thompson , Pramithas Upreti

First-price auctions have recently gained significant traction in digital advertising markets, exemplified by Google's transition from second-price to first-price auctions. Unlike in second-price auctions, where bidding one's private…

Machine Learning · Computer Science 2025-10-07 Zihao Hu , Xiaoyu Fan , Yuan Yao , Jiheng Zhang , Zhengyuan Zhou

Ranking items by their probability of relevance has long been the goal of conventional ranking systems. While this maximizes traditional criteria of ranking performance, there is a growing understanding that it is an oversimplification in…

Information Retrieval · Computer Science 2021-09-14 Lequn Wang , Thorsten Joachims

We describe mechanisms for the allocation of a scarce resource among multiple users in a way that is efficient, fair, and strategy-proof, but when users do not know their resource requirements. The mechanism is repeated for multiple rounds…

Machine Learning · Statistics 2020-12-17 Kirthevasan Kandasamy , Gur-Eyal Sela , Joseph E Gonzalez , Michael I Jordan , Ion Stoica

In this paper, we study online double auctions, where multiple sellers and multiple buyers arrive and depart dynamically to exchange one commodity. We show that there is no deterministic online double auction that is truthful and…

Computer Science and Game Theory · Computer Science 2013-11-04 Dengji Zhao , Dongmo Zhang , Laurent Perrussel

We study an online mixed discrete and continuous optimization problem where a decision maker interacts with an unknown environment for a number of $T$ rounds. At each round, the decision maker needs to first jointly choose a discrete and a…

Optimization and Control · Mathematics 2024-08-27 Lintao Ye , Ming Chi , Zhi-Wei Liu , Xiaoling Wang , Vijay Gupta

In feature-based dynamic pricing, a seller sets appropriate prices for a sequence of products (described by feature vectors) on the fly by learning from the binary outcomes of previous sales sessions ("Sold" if valuation $\geq$ price, and…

Machine Learning · Computer Science 2022-04-04 Jianyu Xu , Yu-Xiang Wang

The use of algorithmic decision making systems in domains which impact the financial, social, and political well-being of people has created a demand for these decision making systems to be "fair" under some accepted notion of equity. This…

Multiagent Systems · Computer Science 2021-12-07 Andrew Estornell , Sanmay Das , Yang Liu , Yevgeniy Vorobeychik

A natural optimization model that formulates many online resource allocation and revenue management problems is the online linear program (LP) in which the constraint matrix is revealed column by column along with the corresponding…

Data Structures and Algorithms · Computer Science 2014-04-10 Shipra Agrawal , Zizhuo Wang , Yinyu Ye

We consider dynamic pricing with covariates under a generalized linear demand model: a seller can dynamically adjust the price of a product over a horizon of $T$ time periods, and at each time period $t$, the demand of the product is…

Machine Learning · Computer Science 2023-11-14 Hanzhao Wang , Kalyan Talluri , Xiaocheng Li