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We consider a discrete-time bipartite matching model with random arrivals of units of supply and demand that can wait in queues located at the nodes in the network. A control policy determines which are matched at each time. The focus is on…

Discrete Mathematics · Computer Science 2016-06-28 Ana Bušić , Sean Meyn

We study the problem of designing voting rules that take as input the ordinal preferences of $n$ agents over a set of $m$ alternatives and output a single alternative, aiming to optimize the overall happiness of the agents. The input to the…

Computer Science and Game Theory · Computer Science 2023-06-01 Vasilis Gkatzelis , Mohamad Latifian , Nisarg Shah

Entities in multi-agent systems may seek conflicting subobjectives, and this leads to competition between them. To address performance degradation due to competition, we consider a bi-level lottery where a social planner at the high level…

Computer Science and Game Theory · Computer Science 2020-12-04 Hunmin Kim , Minghui Zhu

The assortment problem in revenue management is the problem of deciding which subset of products to offer to consumers in order to maximise revenue. A simple and natural strategy is to select the best assortment out of all those that are…

Data Structures and Algorithms · Computer Science 2019-02-22 Gerardo Berbeglia , Gwenaël Joret

We investigate the power of randomness in the context of a fundamental Bayesian optimal mechanism design problem--a single seller aims to maximize expected revenue by allocating multiple kinds of resources to "unit-demand" agents with…

Computer Science and Game Theory · Computer Science 2010-02-24 Shuchi Chawla , David Malec , Balasubramanian Sivan

We show that, in a resource allocation problem, the ex ante aggregate utility of players with cumulative-prospect-theoretic preferences can be increased over deterministic allocations by implementing lotteries. We formulate an optimization…

Theoretical Economics · Economics 2020-12-07 Soham R. Phade , Venkat Anantharam

This paper studies the continuous-time pre-commitment KMM problem proposed by Klibanoff, Marinacci and Mukerji (2005) in incomplete financial markets, which concerns with the portfolio selection under smooth ambiguity. The decision maker…

Mathematical Finance · Quantitative Finance 2023-02-17 Guohui Guan , Zongxia Liang , Yilun Song

This work studies multi-agent sharing optimization problems with the objective function being the sum of smooth local functions plus a convex (possibly non-smooth) function coupling all agents. This scenario arises in many machine learning…

Optimization and Control · Mathematics 2020-06-17 Sulaiman A. Alghunaim , Ming Yan , Ali H. Sayed

We investigate the relationship between product offerings, information dissemination, and consumer decision-making in a monopolistic screening environment in which consumers lack information about their valuation of quality-differentiated…

Theoretical Economics · Economics 2026-04-13 Panagiotis Kyriazis , Edmund Lou

We consider markets consisting of a set of indivisible items, and buyers that have {\em sharp} multi-unit demand. This means that each buyer $i$ wants a specific number $d_i$ of items; a bundle of size less than $d_i$ has no value, while a…

Computer Science and Game Theory · Computer Science 2015-03-13 Ning Chen , Xiaotie Deng , Paul. W. Goldberg , Jinshan Zhang

In this paper we study the problem of maximizing expected utility from the terminal wealth with proportional transaction costs and random endowment. In the context of the existence of consistent price systems, we consider the duality…

Mathematical Finance · Quantitative Finance 2016-09-06 Yiqing Lin , Junjian Yang

Convexity is an important notion in non linear optimization theory as well as in infinite dimensional functional analysis. As will be seen below, very simple and powerful tools will be derived from elementary duality arguments (which are…

Functional Analysis · Mathematics 2020-04-21 Guy Bouchitte

We explore the effects of social influence in a simple market model in which a large number of agents face a binary choice: 'to buy/not to buy' a single unit of a product at a price posted by a single seller (the monopoly case). We consider…

Disordered Systems and Neural Networks · Physics 2008-12-02 Jean-Pierre Nadal , Denis Phan , Mirta B. Gordon , Jean Vannimenus

We study the Constrained Convex Markov Decision Process (MDP), where the goal is to minimize a convex functional of the visitation measure, subject to a convex constraint. Designing algorithms for a constrained convex MDP faces several…

Machine Learning · Computer Science 2024-02-19 Zihao Li , Boyi Liu , Zhuoran Yang , Zhaoran Wang , Mengdi Wang

Adversarial representation learning is a promising paradigm for obtaining data representations that are invariant to certain sensitive attributes while retaining the information necessary for predicting target attributes. Existing…

Machine Learning · Computer Science 2019-12-30 Bashir Sadeghi , Runyi Yu , Vishnu Naresh Boddeti

E-commerce is shifting from search-based shopping to agentic purchasing. Rather than relying on keywords, AI shopping agents learn customer preferences through targeted multi-round conversations and then recommend a tailored set of…

Computer Science and Game Theory · Computer Science 2026-03-24 Shengyu Cao , Ming Hu

Motivated by recent axiomatic developments, we study the risk- and ambiguity-averse investment problem where trading takes place over a fixed finite horizon and terminal payoffs are evaluated according to a criterion defined in terms of a…

Portfolio Management · Quantitative Finance 2013-12-02 Sigrid Källblad

We investigate duality and existence of dual optimizers for several adapted optimal transport problems under minimal assumptions. This includes the causal and bicausal transport, the causal and bicausal barycenter problem, and a…

Probability · Mathematics 2024-11-20 Daniel Kršek , Gudmund Pammer

We study simple and approximately optimal auctions for agents with a particular form of risk-averse preferences. We show that, for symmetric agents, the optimal revenue (given a prior distribution over the agent preferences) can be…

Computer Science and Game Theory · Computer Science 2013-01-04 Hu Fu , Jason Hartline , Darrell Hoy

Algorithmic pricing is the computational problem that sellers (e.g., in supermarkets) face when trying to set prices for their items to maximize their profit in the presence of a known demand. Guruswami et al. (2005) propose this problem…

Computer Science and Game Theory · Computer Science 2008-08-13 Shuchi Chawla , Jason Hartline , Robert Kleinberg
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