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The discrete moment problem is a foundational problem in distribution-free robust optimization, where the goal is to find a worst-case distribution that satisfies a given set of moments. This paper studies the discrete moment problems with…

Optimization and Control · Mathematics 2017-08-08 Xi Chen , Simai He , Bo Jiang , Christopher Thomas Ryan , Teng Zhang

Finding a maximum cut is a fundamental task in many computational settings. Surprisingly, it has been insufficiently studied in the classic distributed settings, where vertices communicate by synchronously sending messages to their…

Data Structures and Algorithms · Computer Science 2017-07-27 Keren Censor-Hillel , Rina Levy , Hadas Shachnai

We consider the problem of estimating the missing mass, partition function or evidence and its probability distribution in the case that for each sample point in the discrete sample space its (unnormalized) probability mass is revealed.…

Statistics Theory · Mathematics 2026-03-16 Bastiaan J. Braams

Stochastic matching is the stochastic version of the well-known matching problem, which consists in maximizing the rewards of a matching under a set of probability distributions associated with the nodes and edges. In most stochastic…

Optimization and Control · Mathematics 2024-05-01 Yuya Hikima , Yasunori Akagi , Hideaki Kim

We consider a matching problem in a bipartite graph $G$ where every vertex has a capacity and a strict preference order on its neighbors. Furthermore, there is a cost function on the edge set. We assume $G$ admits a perfect matching, i.e.,…

Data Structures and Algorithms · Computer Science 2024-11-04 Telikepalli Kavitha , Kazuhisa Makino

We address an optimization problem where the cost function is the expectation of a random mapping. To tackle the problem two approaches based on the approximation of the objective function by consensus-based particle optimization methods on…

Optimization and Control · Mathematics 2025-11-24 Sabrina Bonandin , Michael Herty

Understanding the generative mechanism of a natural system is a vital component of the scientific method. Here, we investigate one of the fundamental steps toward this goal by presenting the minimal generator of an arbitrary binary Markov…

Statistical Mechanics · Physics 2018-02-14 J. Ruebeck , R. G. James , J. R. Mahoney , J. P. Crutchfield

Submodular functions are an important class of functions in combinatorial optimization which satisfy the natural properties of decreasing marginal costs. The study of these functions has led to strong structural properties with applications…

Multiagent Systems · Computer Science 2009-11-13 Gagan Goel , Pushkar Tripathi , Lei Wang

The distinguishing result of this paper is a $\mathbf{P}$-time enumerable partition of all the potential perfect matchings in a bipartite graph. This partition is a set of equivalence classes induced by the missing edges in the potential…

Computational Complexity · Computer Science 2017-10-31 Javaid Aslam

The present paper considers distributed consensus algorithms that involve N agents evolving on a connected compact homogeneous manifold. The agents track no external reference and communicate their relative state according to a…

Optimization and Control · Mathematics 2008-11-27 Alain Sarlette , Rodolphe Sepulchre

Problems of quadratic optimization in Hilbert space often arise when solving ill-posed problems for differential equations. In this case, the target value of the functional is known. In addition, the structure of the functional allows…

Optimization and Control · Mathematics 2025-06-06 N. V. Pletnev

This paper is about minimum cost constrained selection of inputs and outputs for generic arbitrary pole placement. The input-output set is constrained in the sense that the set of states that each input can influence and the set of states…

Optimization and Control · Mathematics 2018-01-11 Shana Moothedath , Prasanna Chaporkar , Madhu N. Belur

The matching problem is a notorious combinatorial optimization problem that has attracted for many years the attention of the statistical physics community. Here we analyze the Euclidean version of the problem, i.e. the optimal matching…

Disordered Systems and Neural Networks · Physics 2017-01-11 Carlo Lucibello , Giorgio Parisi , Gabriele Sicuro

We present an standard constraints generation algorithm to find an explicit set whose robustness is equal to the robustness of the feasible solution set of a combinatorial optimization problem with cost uncertainty. Computational experience…

Optimization and Control · Mathematics 2023-04-11 Alejandro Crema

A dynamic bipartite matching model is given by a bipartite matching graph which determines the possible matchings between the various types of supply and demand items. Both supply and demand items arrive to the system according to a…

Discrete Mathematics · Computer Science 2020-09-11 Arnaud Cadas , Ana Bušić , Josu Doncel

We present an alternating least squares type numerical optimization scheme to estimate conditionally-independent mixture models in $\mathbb{R}^n$, without parameterizing the distributions. Following the method of moments, we tackle an…

Numerical Analysis · Mathematics 2023-08-09 Yifan Zhang , Joe Kileel

The main result of the paper is motivated by the following two, apparently unrelated graph optimization problems: (A) as an extension of Edmonds' disjoint branchings theorem, characterize digraphs comprising $k$ disjoint branchings $B_i$…

Combinatorics · Mathematics 2017-09-05 Kristóf Bérczi , András Frank

Suppose $k$ centers are fit to $m$ points by heuristically minimizing the $k$-means cost; what is the corresponding fit over the source distribution? This question is resolved here for distributions with $p\geq 4$ bounded moments; in…

Machine Learning · Computer Science 2013-11-11 Matus Telgarsky , Sanjoy Dasgupta

We consider the problem of minimizing cost among one-to-one assignments of $n$ jobs onto $n$ machines. The random assignment problem refers to the case when the cost associated with performing jobs on machines are random variables. Aldous…

Disordered Systems and Neural Networks · Physics 2007-05-23 Chandra Nair

We introduce a `concrete complexity' model for studying algorithms for matching in bipartite graphs. The model is based on the "demand query" model used for combinatorial auctions. Most (but not all) known algorithms for bipartite matching…

Computational Complexity · Computer Science 2019-06-12 Noam Nisan