Publications related to Maximizing k-Submodular Functions and Beyond

Performance guarantees for greedy maximization of non-submodular controllability metrics

A key problem in emerging complex cyber-physical networks is the design of information and control topologies, including sensor and actuator selection and communication network design. These problems can be posed as combinatorial set function optimization ...

IEEE2019

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

Ilija Bogunovic

The central task in many interactive machine learning systems can be formalized as the sequential optimization of a black-box function. Bayesian optimization (BO) is a powerful model-based framework for \emph{adaptive} experimentation, where the primary go ...

EPFL2019

New Graph Algorithms via Polyhedral Techniques

Jakub Tarnawski

In this thesis we give new algorithms for two fundamental graph problems. We develop novel ways of using linear programming formulations, even exponential-sized ones, to extract structure from problem instances and to guide algorithms in making progress. S ...

EPFL2019

An Improved Analysis of Local Search for Max-Sum Diversification

Friedrich Eisenbrand, Rico Zenklusen, Alfonso Bolívar Cevallos Manzano

We present new techniques to analyze natural local search algorithms for several variants of the max-sum diversification problem which, in its most basic form, is as follows: given an n-point set X subset of R-d and an integer k, select k points in X so th ...

INFORMS2019

Deterministic Algorithms for Submodular Maximization Problems

Moran Feldman

Randomization is a fundamental tool used in many theoretical and practical areas of computer science. We study here the role of randomization in the area of submodular function maximization. In this area, most algorithms are randomized, and in almost all c ...

ASSOC COMPUTING MACHINERY2018

Robust Maximization of Non-Submodular Objectives

Volkan Cevher, Ilija Bogunovic, Junyao Zhao

We study the problem of maximizing a monotone set function subject to a cardinality constraint k in the setting where some number of elements is deleted from the returned set. The focus of this work is on the worst-case adversarial setting. While there exi ...

2018

Optimal Approximation for Submodular and Supermodular Optimization with Bounded Curvature

Justin Dean Ward

We design new approximation algorithms for the problems of optimizing submodular and supermodular functions subject to a single matroid constraint. Specifically, we consider the case in which we wish to maximize a monotone increasing submodular function or ...

INFORMS2017

Maximizing Symmetric Submodular Functions

Moran Feldman

Symmetric submodular functions are an important family of submodular functions capturing many interesting cases, including cut functions of graphs and hypergraphs. Maximization of such functions subject to various constraints receives little attention by c ...

Association for Computing Machinery2017

Subdeterminant Maximization via Nonconvex Relaxations and Anti-Concentration

Nisheeth Vishnoi, Javad Ebrahimi Boroojeni, Damian Mateusz Straszak

Several fundamental problems that arise in optimization and computer science can be cast as follows: Given vectors v(1), ..., v(m) is an element of R-d and a constraint family B subset of 2([m]), find a set S. B that maximizes the squared volume of the sim ...

Ieee2017

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Slobodan Mitrovic

We study the problem of maximizing a monotone submodular function subject to a cardinality constraint

k

, with the added twist that a number of items

\tau

from the returned set may be removed. We focus on the worst-case setting considered in Orlin et al ...

2017

Maximizing k-Submodular Functions and Beyond

Graph Chatbot

Chat with Graph Search

Performance guarantees for greedy maximization of non-submodular controllability metrics

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

New Graph Algorithms via Polyhedral Techniques

An Improved Analysis of Local Search for Max-Sum Diversification

Deterministic Algorithms for Submodular Maximization Problems

Robust Maximization of Non-Submodular Objectives

Optimal Approximation for Submodular and Supermodular Optimization with Bounded Curvature

Maximizing Symmetric Submodular Functions

Subdeterminant Maximization via Nonconvex Relaxations and Anti-Concentration

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

Maximizing Symmetric Submodular Functions

Performance guarantees for greedy maximization of non-submodular controllability metrics

Deterministic Algorithms for Submodular Maximization Problems

Subdeterminant Maximization via Nonconvex Relaxations and Anti-Concentration

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

New Graph Algorithms via Polyhedral Techniques

Robust Maximization of Non-Submodular Objectives

An Improved Analysis of Local Search for Max-Sum Diversification

Optimal Approximation for Submodular and Supermodular Optimization with Bounded Curvature

Robust Submodular Maximization: A Non-Uniform Partitioning Approach