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Related papers: Combinatorial Prophet Inequalities

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Submodular function minimization (SFM) is a fundamental and efficiently solvable problem class in combinatorial optimization with a multitude of applications in various fields. Surprisingly, there is only very little known about constraint…

Data Structures and Algorithms · Computer Science 2018-11-27 Martin Nägele , Benny Sudakov , Rico Zenklusen

We consider the problem of maximizing submodular functions in single-pass streaming and secretaries-with-shortlists models, both with random arrival order. For cardinality constrained monotone functions, Agrawal, Shadravan, and Stein gave a…

Data Structures and Algorithms · Computer Science 2021-11-16 Paul Liu , Aviad Rubinstein , Jan Vondrak , Junyao Zhao

We explore a prophet inequality problem, where the values of a sequence of items are drawn i.i.d. from some distribution, and an online decision maker must select one item irrevocably. We establish that $\mathrm{CR}_{\ell}$ the worst-case…

Data Structures and Algorithms · Computer Science 2025-01-13 Mathieu Molina , Nicolas Gast , Patrick Loiseau , Vianney Perchet

With the rapid growth of data in modern applications, parallel algorithms for maximizing non-monotone submodular functions have gained significant attention. In the parallel computation setting, the state-of-the-art approximation ratio of…

Data Structures and Algorithms · Computer Science 2025-10-07 Yixin Chen , Wenjing Chen , Alan Kuhnle

We present an optimal, combinatorial 1-1/e approximation algorithm for monotone submodular optimization over a matroid constraint. Compared to the continuous greedy algorithm (Calinescu, Chekuri, Pal and Vondrak, 2008), our algorithm is…

Data Structures and Algorithms · Computer Science 2013-11-20 Yuval Filmus , Justin Ward

We consider the problem of maximizing a monotone submodular function under noise. There has been a great deal of work on optimization of submodular functions under various constraints, resulting in algorithms that provide desirable…

Data Structures and Algorithms · Computer Science 2016-11-08 Avinatan Hassidim , Yaron Singer

In this work we give two new algorithms that use similar techniques for (non-monotone) submodular function maximization subject to a cardinality constraint. The first is an offline fixed parameter tractable algorithm that guarantees a…

Data Structures and Algorithms · Computer Science 2022-04-26 Aviad Rubinstein , Junyao Zhao

In this work we initiate the study of buy-and-sell prophet inequalities. We start by considering what is arguably the most fundamental setting. In this setting the online algorithm observes a sequence of prices one after the other. At each…

Data Structures and Algorithms · Computer Science 2023-05-26 José Correa , Andrés Cristi , Paul Dütting , Mohammad Hajiaghayi , Jan Olkowski , Kevin Schewior

Prophet inequalities are a cornerstone in optimal stopping and online decision-making. Traditionally, they involve the sequential observation of $n$ non-negative independent random variables and face irrevocable accept-or-reject choices.…

Computer Science and Game Theory · Computer Science 2024-08-22 Sebastian Perez-Salazar , Victor Verdugo

Prophet inequalities are performance guarantees for online algorithms (a.k.a. stopping rules) solving the following "hiring problem": a decision maker sequentially inspects candidates whose values are independent random numbers and is asked…

Data Structures and Algorithms · Computer Science 2022-05-23 Makis Arsenis , Robert Kleinberg

We present combinatorial and parallelizable algorithms for maximization of a submodular function, not necessarily monotone, with respect to a size constraint. We improve the best approximation factor achieved by an algorithm that has…

Data Structures and Algorithms · Computer Science 2024-02-21 Yixin Chen , Alan Kuhnle

Budget feasible mechanism considers algorithmic mechanism design questions where there is a budget constraint on the total payment of the mechanism. An important question in the field is that under which valuation domains there exist budget…

Computer Science and Game Theory · Computer Science 2012-03-23 Xiaohui Bei , Ning Chen , Nick Gravin , Pinyan Lu

Submodular functions are a fundamental object of study in combinatorial optimization, economics, machine learning, etc. and exhibit a rich combinatorial structure. Many subclasses of submodular functions have also been well studied and…

Data Structures and Algorithms · Computer Science 2013-04-19 Nikhil R. Devanur , Shaddin Dughmi , Roy Schwartz , Ankit Sharma , Mohit Singh

During the last decade, the matroid secretary problem (MSP) became one of the most prominent classes of online selection problems. Partially linked to its numerous applications in mechanism design, substantial interest arose also in the…

Data Structures and Algorithms · Computer Science 2015-07-31 Moran Feldman , Rico Zenklusen

Optimization problems with set submodular objective functions have many real-world applications. In discrete scenarios, where the same item can be selected more than once, the domain is generalized from a 2-element set to a bounded integer…

Data Structures and Algorithms · Computer Science 2021-11-22 Alberto Schiabel , Vyacheslav Kungurtsev , Jakub Marecek

We propose a theoretical framework to capture incremental solutions to cardinality constrained maximization problems. The defining characteristic of our framework is that the cardinality/support of the solution is bounded by a value…

Discrete Mathematics · Computer Science 2018-04-18 Aaron Bernstein , Yann Disser , Martin Groß

We study the matroid secretary problems with submodular valuation functions. In these problems, the elements arrive in random order. When one element arrives, we have to make an immediate and irrevocable decision on whether to accept it or…

Data Structures and Algorithms · Computer Science 2013-02-27 Tengyu Ma , Bo Tang , Yajun Wang

Symmetric submodular maximization is an important class of combinatorial optimization problems, including MAX-CUT on graphs and hyper-graphs. The state-of-the-art algorithm for the problem over general constraints has an approximation ratio…

Data Structures and Algorithms · Computer Science 2024-06-21 Zongqi Wan , Jialin Zhang , Xiaoming Sun , Zhijie Zhang

We study the single-choice Prophet Inequality problem when the gambler is given access to samples. We show that the optimal competitive ratio of $1/2$ can be achieved with a single sample from each distribution. When the distributions are…

Data Structures and Algorithms · Computer Science 2025-09-12 Aviad Rubinstein , Jack Z. Wang , S. Matthew Weinberg

In a prophet inequality problem, $n$ independent random variables are presented to a gambler one by one. The gambler decides when to stop the sequence and obtains the most recent value as reward. We evaluate a stopping rule by the…

Data Structures and Algorithms · Computer Science 2023-11-16 Andrés Cristi , Bruno Ziliotto
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