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Related papers: A Note on M-convex Functions on Jump Systems

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Jump systems are sets of integer vectors satisfying a simple axiom, generalizing matroids, also delta-matroids, and well-kown combinatorial examples such as degree sequences of subgraphs of a graph. It is useful to know if a set of vectors…

Combinatorics · Mathematics 2023-02-28 Mouna Sadli , András Sebő

Integrally convex functions constitute a fundamental function class in discrete convex analysis, including M-convex functions, L-convex functions, and many others. This paper aims at a rather comprehensive survey of recent results on…

Combinatorics · Mathematics 2023-02-23 Kazuo Murota , Akihisa Tamura

In discrete convex analysis, various convexity concepts are considered for discrete functions such as separable convexity, L-convexity, M-convexity, integral convexity, and multimodularity. These concepts of discrete convex functions are…

Combinatorics · Mathematics 2023-02-06 Satoko Moriguchi , Kazuo Murota

Discrete convex functions are used in many areas, including operations research, discrete-event systems, game theory, and economics. The objective of this paper is to investigate basic operations such as direct sum, splitting, and…

Optimization and Control · Mathematics 2020-08-31 Kazuo Murota

Murota (1998) and Murota and Shioura (1999) introduced concepts of M-convex function and M${}^\natural$-convex function as discrete convex functions, which are generalizations of valuated matroids due to Dress and Wenzel (1992). In the…

Combinatorics · Mathematics 2020-05-27 Satoru Fujishige , Hiroshi Hirai

L$^\natural$ (natural)-convex functions encompass a large class of nonlinear functions over general integer domains and arise in a wide range of real-world applications. We explore the minimization of L$^\natural$-convex functions, of…

Optimization and Control · Mathematics 2025-11-26 Qimeng Yu , Simge Küçükyavuz

Markov jump processes are continuous-time stochastic processes which describe dynamical systems evolving in discrete state spaces. These processes find wide application in the natural sciences and machine learning, but their inference is…

Machine Learning · Computer Science 2025-03-05 David Berghaus , Kostadin Cvejoski , Patrick Seifner , Cesar Ojeda , Ramses J. Sanchez

For a function defined on a convex set in a Euclidean space, midpoint convexity is the property requiring that the value of the function at the midpoint of any line segment is not greater than the average of its values at the endpoints of…

Metric Geometry · Mathematics 2019-05-20 Satoko Moriguchi , Kazuo Murota , Akihisa Tamura , Fabio Tardella

For continuous functions, midpoint convexity characterizes convex functions. By considering discrete versions of midpoint convexity, several types of discrete convexities of functions, including integral convexity, L$^\natural$-convexity…

Optimization and Control · Mathematics 2020-02-03 Akihisa Tamura , Kazuya Tsurumi

Multimodular functions, primarily used in the literature of queueing theory, discrete-event systems, and operations research, constitute a fundamental function class in discrete convex analysis. The objective of this paper is to clarify the…

Optimization and Control · Mathematics 2019-06-25 Satoko Moriguchi , Kazuo Murota

We unify the study of quotients of matroids, polymatroids, valuated matroids and strong maps of submodular functions in the framework of Murota's discrete convex analysis. As a main result, we compile a list of ten equivalent…

Combinatorics · Mathematics 2025-09-04 Marie-Charlotte Brandenburg , Georg Loho , Ben Smith

This paper presents discrete convex analysis as a tool for economics and game theory. Discrete convex analysis is a new framework of discrete mathematics and optimization, developed during the last two decades. Recently, it is being…

Combinatorics · Mathematics 2022-12-08 Kazuo Murota

Discrete convex functions are used in many areas, including operations research, discrete-event systems, game theory, and economics. The objective of this paper is to offer a survey on fundamental operations for various kinds of discrete…

Combinatorics · Mathematics 2019-10-04 Kazuo Murota

Submodular Functions are a special class of set functions, which generalize several information-theoretic quantities such as entropy and mutual information [1]. Submodular functions have subgradients and subdifferentials [2] and admit…

Discrete Mathematics · Computer Science 2020-07-01 Rishabh Iyer , Jeff Bilmes

Discrete Fenchel duality is one of the central issues in discrete convex analysis. The Fenchel-type min-max theorem for a pair of integer-valued M-natural-convex functions generalizes the min-max formulas for polymatroid intersection and…

Combinatorics · Mathematics 2021-12-07 Kazuo Murota , Akihisa Tamura

The velocity-jump model is a specific type of piecewise deterministic Markov process in which an individual's velocity is constant except at times that form the events of some point process. It represents an interpretable continuous-time…

Methodology · Statistics 2025-09-26 Paul G. Blackwell

A fundamental theorem in discrete convex analysis states that a set function is M$^\natural$-concave if and only if its conjugate function is submodular. This paper gives a new proof to this fact.

Combinatorics · Mathematics 2022-12-14 Kazuo Murota , Akiyoshi Shioura

Murota et al. have recently developed a theory of discrete convex analysis which concerns M-convex functions on jump systems. We introduce here a family of M-concave functions arising naturally from polynomials (over a field of generalized…

Combinatorics · Mathematics 2012-04-18 Petter Brändén

This paper is devoted to a study of mathematical structures arising from choice functions satisfying the path independence property (Plott functions). We broaden the notion of a choice function by allowing of empty choice. This enables us…

Combinatorics · Mathematics 2007-05-23 V. I. Danilov , G. A. Koshevoy

We consider the problem of detecting jumps in an otherwise smoothly evolving trend whilst the covariance and higher-order structures of the system can experience both smooth and abrupt changes over time. The number of jump points is allowed…

Methodology · Statistics 2023-12-27 Weichi Wu , Zhou Zhou
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