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Maximum diversity aims at selecting a diverse set of high-quality objects from a collection, which is a fundamental problem and has a wide range of applications, e.g., in Web search. Diversity under a uniform or partition matroid constraint…

Data Structures and Algorithms · Computer Science 2021-04-13 Guangyi Zhang , Aristides Gionis

Motivated by online settings where users can provide explicit feedback about the relevance of products that are sequentially presented to them, we look at the recommendation process as a problem of dynamically optimizing this relevance…

Machine Learning · Computer Science 2015-03-09 Vijay Kamble , Nadia Fawaz , Fernando Silveira

We study a variant of classical clustering formulations in the context of algorithmic fairness, known as diversity-aware clustering. In this variant we are given a collection of facility subsets, and a solution must contain at least a…

Data Structures and Algorithms · Computer Science 2022-10-25 Suhas Thejaswi , Ameet Gadekar , Bruno Ordozgoiti , Michal Osadnik

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

We study the interplay of fairness, welfare, and equity considerations in personalized pricing based on customer features. Sellers are increasingly able to conduct price personalization based on predictive modeling of demand conditional on…

Machine Learning · Computer Science 2020-12-29 Nathan Kallus , Angela Zhou

Dynamic pricing is commonly used to regulate congestion in shared service systems. This paper is motivated by the fact that in the presence of users with varying price sensitivity (responsiveness), conventional monotonic pricing can lead to…

Systems and Control · Electrical Eng. & Systems 2026-03-24 Yingqing Chen , Anni Li , Christos G. Cassandras , Homayoun Hamedmoghadam , Fabian Wirth , Robert Shorten

The existing literature on optimal auctions focuses on optimizing the expected revenue of the seller, and is appropriate for risk-neutral sellers. In this paper, we identify good mechanisms for risk-averse sellers. As is standard in the…

Computer Science and Game Theory · Computer Science 2010-04-02 Mukund Sundararajan , Qiqi Yan

This paper describes a novel approach to planning which takes advantage of decision theory to greatly improve robustness in an uncertain environment. We present an algorithm which computes conditional plans of maximum expected utility. This…

Artificial Intelligence · Computer Science 2013-02-28 Stephen G. Pimentel , Lawrence M. Brem

This paper studies a {\it reversible} investment problem where a social planner aims to control its capacity production in order to fit optimally the random demand of a good. Our model allows for general diffusion dynamics on the demand as…

Probability · Mathematics 2013-07-08 Salvatore Federico , Huyen Pham

In the present paper, several types of efficiency conditions are established for vector optimization problems with cone constraints affected by uncertainty, but with no information of stochastic nature about the uncertain data. Following a…

Optimization and Control · Mathematics 2021-02-01 Amos Uderzo

In this paper we consider the problem of pricing multiple differentiated products. This is challenging as a price change in one product, not only changes the demand of that particular product, but also the demand for the other products. To…

Optimization and Control · Mathematics 2017-10-27 Ruben van de Geer , Sandjai Bhulai

A canonical setting for non-monetary online resource allocation is one where agents compete over multiple rounds for a single item per round, with i.i.d. valuations and additive utilities across rounds. With $n$ symmetric agents, a natural…

Computer Science and Game Theory · Computer Science 2025-12-01 David X. Lin , Giannis Fikioris , Siddhartha Banerjee , Éva Tardos

In the photonic design problem, a scientist or engineer chooses the physical parameters of a device to best match some desired device behavior. Many instances of the photonic design problem can be naturally stated as a mathematical…

Computational Physics · Physics 2021-01-13 Guillermo Angeris , Jelena Vučković , Stephen Boyd

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

Designing fair algorithmic decision systems requires balancing model performance with fairness toward affected individuals: More fairness might require sacrificing some performance and vice versa, yet the space of possible trade-offs is…

Machine Learning · Computer Science 2026-05-12 Mieke Wilms , Christoph Heitz

I characterize optimal government policy in a sticky-price economy with different types of consumers and endogenous financial constraints in the banking and entrepreneurial sectors. The competitive equilibrium allocation is constrained…

General Economics · Economics 2025-01-29 Aliaksandr Zaretski

A recent line of research has established a novel desideratum for designing approximately-revenue-optimal multi-item mechanisms, namely the buy-many constraint. Under this constraint, prices for different allocations made by the mechanism…

Computer Science and Game Theory · Computer Science 2024-05-17 Shuchi Chawla , Rojin Rezvan , Yifeng Teng , Christos Tzamos

A monopolist wishes to maximize her profits by finding an optimal price policy. After she announces a menu of products and prices, each agent $x$ will choose to buy that product $y(x)$ which maximizes his own utility, if positive. The…

Optimization and Control · Mathematics 2021-02-12 Robert J. McCann , Kelvin Shuangjian Zhang

We consider a settings of hierarchical reinforcement learning, in which the reward is a sum of components. For each component we are given a policy that maximizes it and our goal is to assemble a policy from the individual policies that…

Machine Learning · Computer Science 2020-01-06 Tom Zahavy , Avinatan Hasidim , Haim Kaplan , Yishay Mansour

Selling a single item to $n$ self-interested buyers is a fundamental problem in economics, where the two objectives typically considered are welfare maximization and revenue maximization. Since the optimal mechanisms are often impractical…

Computer Science and Game Theory · Computer Science 2024-11-06 Billy Jin , Thomas Kesselheim , Will Ma , Sahil Singla
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