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We study the two-agent single-item bilateral trade. Ideally, the trade should happen whenever the buyer's value for the item exceeds the seller's cost. However, the classical result of Myerson and Satterthwaite showed that no mechanism can…

Computer Science and Game Theory · Computer Science 2022-05-03 Yumou Fei

In this work, we consider robust submodular maximization with matroid constraints. We give an efficient bi-criteria approximation algorithm that outputs a small family of feasible sets whose union has (nearly) optimal objective value. This…

Data Structures and Algorithms · Computer Science 2018-07-26 Sebastian Pokutta , Mohit Singh , Alfredo Torrico

We study a classic Bayesian mechanism design setting of monopoly problem for an additive buyer in the presence of budgets. In this setting a monopolist seller with $m$ heterogeneous items faces a single buyer and seeks to maximize her…

Computer Science and Game Theory · Computer Science 2018-10-09 Yu Cheng , Nick Gravin , Kamesh Munagala , Kangning Wang

The classical problem of maximizing a submodular function under a matroid constraint is considered. Defining a new measure for the increments made by the greedy algorithm at each step, called the discriminant, improved approximation ratio…

Data Structures and Algorithms · Computer Science 2018-10-31 Nived Rajaraman , Rahul Vaze

We propose a simple randomized rule for the optimization of prices in revenue management with contextual information. It is known that the certainty equivalent pricing rule, albeit popular, is sub-optimal. We show that, by allowing a small…

Computer Science and Game Theory · Computer Science 2020-10-26 Neil Walton , Yuqing Zhang

We construct prior-free auctions with constant-factor approximation guarantees with ordered bidders, in both unlimited and limited supply settings. We compare the expected revenue of our auctions on a bid vector to the monotone price…

Computer Science and Game Theory · Computer Science 2012-12-13 Elias Koutsoupias , Stefano Leonardi , Tim Roughgarden

We study the problem of computing maximin share guarantees, a recently introduced fairness notion. Given a set of $n$ agents and a set of goods, the maximin share of a single agent is the best that she can guarantee to herself, if she would…

Computer Science and Game Theory · Computer Science 2018-06-12 Georgios Amanatidis , Evangelos Markakis , Afshin Nikzad , Amin Saberi

We study an online fair division setting, where goods arrive one at a time and there is a fixed set of $n$ agents, each of whom has an additive valuation function over the goods. Once a good appears, the value each agent has for it is…

Computer Science and Game Theory · Computer Science 2025-05-29 Georgios Amanatidis , Alexandros Lolos , Evangelos Markakis , Victor Turmel

We provide a computationally efficient black-box reduction from mechanism design to algorithm design in very general settings. Specifically, we give an approximation-preserving reduction from truthfully maximizing \emph{any} objective under…

Computer Science and Game Theory · Computer Science 2013-05-20 Yang Cai , Constantinos Daskalakis , S. Matthew Weinberg

In this paper, we study the two-facility location game on a line with optional preference where the acceptable set of facilities for each agent could be different and an agent's cost is his distance to the closest facility within his…

Data Structures and Algorithms · Computer Science 2019-07-23 Minming Li , Pinyan Lu , Yuhao Yao , Jialin Zhang

We present a polynomial-time $\frac{3}{2}$-approximation algorithm for the problem of finding a maximum-cardinality stable matching in a many-to-many matching model with ties and laminar constraints on both sides. We formulate our problem…

Data Structures and Algorithms · Computer Science 2021-10-06 Yu Yokoi

In the problem called single resource constraint scheduling, we are given $m$ identical machines and a set of jobs, each needing one machine to be processed as well as a share of a limited renewable resource $R$. A schedule of these jobs is…

Data Structures and Algorithms · Computer Science 2021-07-06 Klaus Jansen , Malin Rau

Inspired by regularization techniques in statistics and machine learning, we study complementary composite minimization in the stochastic setting. This problem corresponds to the minimization of the sum of a (weakly) smooth function endowed…

Machine Learning · Computer Science 2024-01-24 Alexandre d'Aspremont , Cristóbal Guzmán , Clément Lezane

We study multi-buyer multi-item sequential item pricing mechanisms for revenue maximization with the goal of approximating a natural fractional relaxation -- the ex ante optimal revenue. We assume that buyers' values are subadditive but…

Computer Science and Game Theory · Computer Science 2024-04-24 Shuchi Chawla , Dimitris Christou , Trung Dang , Zhiyi Huang , Gregory Kehne , Rojin Rezvan

The improving multi-armed bandits problem is a formal model for allocating effort under uncertainty, motivated by scenarios such as investing research effort into new technologies, performing clinical trials, and hyperparameter selection…

Machine Learning · Computer Science 2026-05-22 Avrim Blum , Marten Garicano , Kavya Ravichandran , Dravyansh Sharma

We introduce a dynamic mechanism design problem in which the designer wants to offer for sale an item to an agent, and another item to the same agent at some point in the future. The agent's joint distribution of valuations for the two…

Computer Science and Game Theory · Computer Science 2023-05-22 Christos Papadimitriou , George Pierrakos , Christos-Alexandros Psomas , Aviad Rubinstein

We consider a monopolist seller facing a single buyer with additive valuations over n heterogeneous, independent items. It is known that in this important setting optimal mechanisms may require randomization [HR12], use menus of infinite…

Computer Science and Game Theory · Computer Science 2015-11-17 Aviad Rubinstein

We make three different types of contributions to cost-sharing: First, we identify several new classes of combinatorial cost functions that admit incentive-compatible mechanisms achieving both a constant-factor approximation of…

Computer Science and Game Theory · Computer Science 2007-05-23 Tim Roughgarden , Mukund Sundararajan

The challenge of identifying the best feasible arm within a fixed budget has attracted considerable interest in recent years. However, a notable gap remains in the literature: the exact exponential rate at which the error probability…

Machine Learning · Computer Science 2025-06-04 Jie Bian , Vincent Y. F. Tan

Auto-bidding systems are widely used in advertising to automatically determine bid values under constraints such as total budget and Return-on-Spend (RoS) targets. Existing works often assume that the value of an ad impression, such as the…

Machine Learning · Computer Science 2026-02-03 Jiale Han , Chun Gan , Chengcheng Zhang , Jie He , Zhangang Lin , Ching Law , Xiaowu Dai
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