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We present a branch and bound method for maximizing an arbitrary set function h mapping 2^V to R. By decomposing h as f-g, where f is a submodular function and g is the cut function of a (simple, undirected) graph G with vertex set V, our…

Combinatorics · Mathematics 2009-06-02 Kevin Byrnes

Submodular function minimization is well studied, and existing algorithms solve it exactly or up to arbitrary accuracy. However, in many applications, such as structured sparse learning or batch Bayesian optimization, the objective function…

Machine Learning · Computer Science 2022-03-10 Marwa El Halabi , Stefanie Jegelka

Modular Decomposition focuses on repeatedly identifying a module M (a collection of vertices that shares exactly the same neighbourhood outside of M) and collapsing it into a single vertex. This notion of exactitude of neighbourhood is very…

Discrete Mathematics · Computer Science 2021-01-25 Michel Habib , Lalla Mouatadid , Eric Sopena , Mengchuan Zou

We present the first near-linear work and poly-logarithmic depth algorithm for computing a minimum cut in a graph, while previous parallel algorithms with poly-logarithmic depth required at least quadratic work in the number of vertices. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-03 Barbara Geissmann , Lukas Gianinazzi

In this paper, we propose novel algorithms for inferring the Maximum a Posteriori (MAP) solution of discrete pairwise random field models under multiple constraints. We show how this constrained discrete optimization problem can be…

Machine Learning · Computer Science 2013-08-02 Yongsub Lim , Kyomin Jung , Pushmeet Kohli

Two seemingly unrelated problems, scheduling a multiclass queueing system and minimizing a submodular function, share a rather deep connection via the polymatroid that is characterized by a submodular set function on the one hand and…

Optimization and Control · Mathematics 2008-05-09 Yingdong Lu , David Yao

A highly influential ingredient of many techniques designed to exploit sparsity in numerical optimization is the so-called chordal extension of a graph representation of the optimization problem. The definitive relation between chordal…

Machine Learning · Computer Science 2019-10-18 Defeng Liu , Andrea Lodi , Mathieu Tanneau

A natural and important generalization of submodularity -- $k$-submodularity -- applies to set functions with $k$ arguments and appears in a broad range of applications, such as infrastructure design, machine learning, and healthcare. In…

Optimization and Control · Mathematics 2021-06-29 Qimeng Yu , Simge Küçükyavuz

Let $f:2^{E} \rightarrow \mathbb{Z}_+$ be a submodular function on a ground set $E = [n]$, and let $P(f)$ denote its extended polymatroid. Given a direction $d \in \mathbb{Z}^n$ with at least one positive entry, the line search problem is…

Optimization and Control · Mathematics 2026-03-10 Swati Gupta , Alec Zhu

We present a deterministic way of assigning small (log bit) weights to the edges of a bipartite planar graph so that the minimum weight perfect matching becomes unique. The isolation lemma as described in (Mulmuley et al. 1987) achieves the…

Data Structures and Algorithms · Computer Science 2008-02-21 Samir Datta , Raghav Kulkarni , Sambuddha Roy

The notion of singular reduction modules, i.e., of singular modules of nonclassical (conditional) symmetry, of differential equations is introduced. It is shown that the derivation of nonclassical symmetries for differential equations can…

Mathematical Physics · Physics 2017-12-05 Vaycheslav M. Boyko , Michael Kunzinger , Roman O. Popovych

Submodular width is a central structural measure governing the complexity of conjunctive query evaluation. In this paper we recast submodular width in geometric terms. We how that submodular width can be approximated, up to a factor $3/2$,…

Data Structures and Algorithms · Computer Science 2026-04-27 Matthias Lanzinger

This paper studies the problem of selecting a submatrix of a positive definite matrix in order to achieve a desired bound on the smallest eigenvalue of the submatrix. Maximizing this smallest eigenvalue has applications to selecting input…

Systems and Control · Computer Science 2017-09-08 Andrew Clark , Qiqiang Hou , Linda Bushnell , Radha Poovendran

We introduce multiple symmetric LP relaxations for minimum cut problems. The relaxations give optimal and approximate solutions when the input is a Hamiltonian cycle. We show that this leads to one of two interesting results. In one case,…

Data Structures and Algorithms · Computer Science 2020-05-26 Robert D. Carr , Jennifer Iglesias , Giuseppe Lanciac , Benjamin Moseley

In this paper, we present efficient pseudodeterministic algorithms for both the global minimum cut and minimum s-t cut problems. The running time of our algorithm for the global minimum cut problem is asymptotically better than the fastest…

Data Structures and Algorithms · Computer Science 2025-12-30 Aryan Agarwala , Nithin Varma

We present the first mini-batch algorithm for maximizing a non-negative monotone decomposable submodular function, $F=\sum_{i=1}^N f^i$, under a set of constraints. We consider two sampling approaches: uniform and weighted. We first show…

Machine Learning · Computer Science 2024-10-03 Gregory Schwartzman

We study the problem of minimizing a convex function on a nonempty, finite subset of the integer lattice when the function cannot be evaluated at noninteger points. We propose a new underestimator that does not require access to…

Optimization and Control · Mathematics 2021-08-19 Jeffrey Larson , Sven Leyffer , Prashant Palkar , Stefan M. Wild

In a capacitated directed graph, it is known that the set of all min-cuts forms a distributive lattice [1], [2]. Here, we describe this lattice as a regular predicate whose forbidden elements can be advanced in constant parallel time after…

Data Structures and Algorithms · Computer Science 2025-12-23 Robert Streit , Vijay K. Garg

We present the first work-optimal polylogarithmic-depth parallel algorithm for the minimum cut problem on non-sparse graphs. For $m\geq n^{1+\epsilon}$ for any constant $\epsilon>0$, our algorithm requires $O(m \log n)$ work and $O(\log^3…

Data Structures and Algorithms · Computer Science 2021-02-19 Andrés López-Martínez , Sagnik Mukhopadhyay , Danupon Nanongkai

In this short note we prove a lower bound for the MaxCut of a graph in terms of the Lov\'asz theta function of its complement. We combine this with known bounds on the Lov\'asz theta function of complements of $H$-free graphs to recover…

Combinatorics · Mathematics 2023-09-12 Igor Balla , Oliver Janzer , Benny Sudakov