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Related papers: Mechanism Design for Maximum Vectors

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Constrained submodular set function maximization problems often appear in multi-agent decision-making problems with a discrete feasible set. A prominent example is the problem of multi-agent mobile sensor placement over a discrete domain.…

Optimization and Control · Mathematics 2021-08-02 Navid Rezazadeh , Solmaz S. Kia

Given a graph $G$, an integer $k\geq 0$, and a non-negative integral function $f:V(G) \rightarrow \mathcal{N}$, the Vector Domination problem asks whether a set $S$ of vertices, of cardinality $k$ or less, exists in $G$ so that every vertex…

Combinatorics · Mathematics 2025-06-19 Mahabba El Sahili , Faisal N. Abu-Khzam

This document introduces a strategy to solve linear optimization problems. The strategy is based on the bounding condition each constraint produces on each one of the problem's dimension. The solution of a linear optimization problem is…

Optimization and Control · Mathematics 2018-09-24 Gerardo L. Febres

Nondominated sorting is a discrete process that sorts points in Euclidean space according to the coordinatewise partial order, and is used to rank feasible solutions to multiobjective optimization problems. It was previously shown that…

Analysis of PDEs · Mathematics 2022-05-18 Brendan Cook , Jeff Calder

Combining quantum computers with classical compute power has become a standard means for developing algorithms that are eventually supposed to beat any purely classical alternatives. While in-principle advantages for solution quality or…

Quantum Physics · Physics 2026-01-23 Simon Thelen , Wolfgang Mauerer

We describe algorithms, and experimental strategies, for the Pareto optimal control problem of simultaneously driving an arbitrary number of quantum observable expectation values to their respective extrema. Conventional quantum optimal…

Quantum Physics · Physics 2009-11-13 Raj Chakrabarti , Rebing Wu , Herschel Rabitz

Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior…

Computer Science and Game Theory · Computer Science 2015-03-19 Kevin Waugh , Brian D. Ziebart , J. Andrew Bagnell

We study incentive design when multiple principals simultaneously design mechanisms for their respective teams in environments with strategic spillovers. In this environment, each principal's set of incentive-compatible mechanisms--those…

Theoretical Economics · Economics 2026-05-11 Brian Roberson

It is known that problems like Vertex Cover, Feedback Vertex Set and Odd Cycle Transversal are polynomial time solvable in the class of chordal graphs. We consider these problems in a graph that has at most $k$ vertices whose deletion…

Data Structures and Algorithms · Computer Science 2020-02-25 Ashwin Jacob , Fahad Panolan , Venkatesh Raman , Vibha Sahlot

We consider the information design problem in spatial resource competition settings. Agents gather at a location deciding whether to move to another location for possibly higher level of resources, and the utility each agent gets by moving…

Computer Science and Game Theory · Computer Science 2019-09-30 Pu Yang , Krishnamurthy Iyer , Peter Frazier

The key contribution of the paper is a comprehensive study of the egalitarian mechanism with respect to manipulation by a coalition of agents. Our main result is that the egalitarian mechanism is, in fact, peak group strategyproof : no…

Computer Science and Game Theory · Computer Science 2011-07-25 Shyam S Chandramouli , Jay Sethuraman

We introduce a framework for comparing the privacy of different mechanisms. A mechanism designer employs a dynamic protocol to elicit agents' private information. Protocols produce a set of contextual privacy violations -- information…

Theoretical Economics · Economics 2025-12-29 Andreas Haupt , Zoë Hitzig

We study a multi-round welfare-maximising mechanism design problem in instances where agents do not know their values. On each round, a mechanism first assigns an allocation each to a set of agents and charges them a price; at the end of…

Machine Learning · Statistics 2022-01-25 Kirthevasan Kandasamy , Joseph E. Gonzalez , Michael I. Jordan , Ion Stoica

An algorithm which computes a solution of a set optimization problem is provided. The graph of the objective map is assumed to be given by finitely many linear inequalities. A solution is understood to be a set of points in the domain…

Optimization and Control · Mathematics 2014-05-29 Andreas Löhne , Carola Schrage

Constrained maximization of submodular functions poses a central problem in combinatorial optimization. In many realistic scenarios, a number of agents need to maximize multiple submodular objectives over the same ground set. We study such…

Data Structures and Algorithms · Computer Science 2024-07-22 Georgios Amanatidis , Georgios Birmpas , Philip Lazos , Stefano Leonardi , Rebecca Reiffenhäuser

We consider the problem of controlling an unknown linear dynamical system in the presence of (nonstochastic) adversarial perturbations and adversarial convex loss functions. In contrast to classical control, the a priori determination of an…

Machine Learning · Computer Science 2020-01-22 Elad Hazan , Sham M. Kakade , Karan Singh

We address the design and synthesis of optimal control strategies for high-dimensional stochastic dynamical systems. Such systems may be deterministic nonlinear systems evolving from random initial states, or systems driven by random…

Numerical Analysis · Mathematics 2020-08-26 Panos Lambrianides , Qi Gong , Daniele Venturi

A variant of the classical knapsack problem is considered in which each item is associated with an integer weight and a qualitative level. We define a dominance relation over the feasible subsets of the given item set and show that this…

Data Structures and Algorithms · Computer Science 2020-02-13 Luca E. Schäfer , Tobias Dietz , Maria Barbati , José Rui Figueira , Salvatore Greco , Stefan Ruzika

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 investigate the problem of classifying feature vectors with mutually independent but non-identically distributed elements. First, we show the importance of this problem. Next, we propose a classifier and derive an…

Machine Learning · Computer Science 2021-09-01 Farzad Shahrivari , Nikola Zlatanov
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