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A number of discrete and continuous optimization problems in machine learning are related to convex minimization problems under submodular constraints. In this paper, we deal with a submodular function with a directed graph structure, and…

Machine Learning · Computer Science 2013-09-27 Kiyohito Nagano , Yoshinobu Kawahara

Submodular optimization has received significant attention in both practice and theory, as a wide array of problems in machine learning, auction theory, and combinatorial optimization have submodular structure. In practice, these problems…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-04 Paul Liu , Jan Vondrak

In this paper we design a new primal-dual algorithm for the classic discrete optimization problem of maximizing a monotone submodular function subject to a cardinality constraint achieving the optimal approximation of $(1-1/e)$. This…

Data Structures and Algorithms · Computer Science 2023-11-15 Deeparnab Chakrabarty , Luc Cote

Consider the following generalization of the classic binary search problem: a searcher is required to find a hidden vertex $x$ in a tree $T$. To do so, they iteratively perform queries to an oracle, each about a chosen vertex $v$. After…

Data Structures and Algorithms · Computer Science 2025-10-01 Michał Szyfelbein

Balkanski and Singer [5] recently initiated the study of adaptivity (or parallelism) for constrained submodular function maximization, and studied the setting of a cardinality constraint. Very recent improvements for this problem by…

Data Structures and Algorithms · Computer Science 2018-11-20 Chandra Chekuri , Kent Quanrud

In graph theory, Courcelle's theorem essentially states that, if an algorithmic problem can be formulated in monadic second-order logic, then it can be solved in linear time for graphs of bounded treewidth. We prove such a metatheorem for a…

Geometric Topology · Mathematics 2014-03-13 Benjamin A. Burton , Rodney G. Downey

Motivated by the increasing need to understand the algorithmic foundations of distributed large-scale graph computations, we study a number of fundamental graph problems in a message-passing model for distributed computing where $k \geq 2$…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-07-07 Gopal Pandurangan , Peter Robinson , Michele Scquizzato

Optimal Transport (OT) problems arise in a wide range of applications, from physics to economics. Getting numerical approximate solution of these problems is a challenging issue of practical importance. In this work, we investigate the…

Probability · Mathematics 2019-05-15 Aurélien Alfonsi , Rafaël Coyaud , Virginie Ehrlacher , Damiano Lombardi

Algorithmic meta-theorems state that problems definable in a fixed logic can be solved efficiently on structures with certain properties. An example is Courcelle's Theorem, which states that all problems expressible in monadic second-order…

Logic in Computer Science · Computer Science 2025-01-09 Max Bannach , Markus Hecher

We study the problem of maximizing a non-monotone, non-negative submodular function subject to a matroid constraint. The prior best-known deterministic approximation ratio for this problem is $\frac{1}{4}-\epsilon$ under…

Data Structures and Algorithms · Computer Science 2020-10-23 Kai Han , Zongmai Cao , Shuang Cui , Benwei Wu

In this paper, we propose the first continuous optimization algorithms that achieve a constant factor approximation guarantee for the problem of monotone continuous submodular maximization subject to a linear constraint. We first prove that…

Data Structures and Algorithms · Computer Science 2020-06-23 Moran Feldman , Amin Karbasi

We study graph partitioning problems from a min-max perspective, in which an input graph on n vertices should be partitioned into k parts, and the objective is to minimize the maximum number of edges leaving a single part. The two main…

Data Structures and Algorithms · Computer Science 2011-10-21 Nikhil Bansal , Uriel Feige , Robert Krauthgamer , Konstantin Makarychev , Viswanath Nagarajan , Joseph , Naor , Roy Schwartz

We study the recently introduced idea of worst-case sensitivity for monotone submodular maximization with cardinality constraint $k$, which captures the degree to which the output argument changes on deletion of an element in the input. We…

Data Structures and Algorithms · Computer Science 2020-10-12 Conor McMeel , Yuichi Yoshida

We present semi-streaming algorithms for basic graph problems that have optimal per-edge processing times and therefore surpass all previous semi-streaming algorithms for these tasks. The semi-streaming model, which is appropriate when…

Discrete Mathematics · Computer Science 2007-09-03 Mariano Zelke

We develop an approach for solving one-sided optimal stopping problems in discrete time for general underlying Markov processes on the real line. The main idea is to transform the problem into an auxiliary problem for the ladder height…

Probability · Mathematics 2018-10-29 Sören Christensen , Albrecht Irle

We study partial and budgeted versions of the well studied connected dominating set problem. In the partial connected dominating set problem, we are given an undirected graph G = (V,E) and an integer n', and the goal is to find a minimum…

Data Structures and Algorithms · Computer Science 2013-11-12 Samir Khuller , Manish Purohit , Kanthi Sarpatwar

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

We introduce the following submodular generalization of the Shortest Cycle problem. For a nonnegative monotone submodular cost function $f$ defined on the edges (or the vertices) of an undirected graph $G$, we seek for a cycle $C$ in $G$ of…

Data Structures and Algorithms · Computer Science 2022-11-10 Fedor V. Fomin , Petr A. Golovach , Tuukka Korhonen , Daniel Lokshtanov , Giannos Stamoulis

Non-monotone constrained submodular maximization plays a crucial role in various machine learning applications. However, existing algorithms often struggle with a trade-off between approximation guarantees and practical efficiency. The…

Machine Learning · Computer Science 2024-05-24 Murad Tukan , Loay Mualem , Moran Feldman

We study fully dynamic algorithms for maximum matching. This is a well-studied problem, known to admit several update-time/approximation trade-offs. For instance, it is known how to maintain a 1/2-approximate matching in $\log^{O(1)} n$…

Data Structures and Algorithms · Computer Science 2022-11-15 Soheil Behnezhad