Results 91 to 100 of about 10,146,366 (200)
Risk-Sensitive Submodular Optimization
, 2018 The conditional value at risk (CVaR) is a popular risk measure which enables risk-averse decision making under uncertainty. We consider maximizing the CVaR of a continuous submodular function, an extension of submodular set functions to a continuous ...
Wilder, Bryan, Bryan Wilder
core +1 more source
Submodular functions on diamonds
, 2008 Let V be a finite set. A set function f : 2V → R is said to be submodular if for all A,B ⊆ V we have f(A∪B)+f(A∩B) ≤ f(A)+f(B). Submodular set functions have been studied extensively and examples of such functions include the cut function of graphs and ...
Kuivinen, Fredrik,
core
Regularized Unconstrained Weakly Submodular Maximization [PDF]
Submodular optimization finds applications in machine learning and data mining. In this paper, we study the problem of maximizing functions of the form $h = f-c$, where $f$ is a monotone, non-negative, weakly submodular set function and $c$ is a modular ...
Basu, Samik, Zhu, Yanhui, Pavan, A.
core +1 more source
Submodular maximization over multiple matroids via generalized exchange properties
, 2009 In this paper, we consider the problem of maximizing a non-negative submodular function f, defined on a (finite) ground set N, subject to matroid constraints.
Jon Lee +5 more
core +1 more source
A Polynomial Algorithm for Minimizing $k$-Distant Submodular Functions [PDF]
This paper considers the minimization problem of relaxed submodular functions. For a positive integer $k$, a set function is called $k$-distant submodular if the submodular inequality holds for every pair whose symmetric difference is at least $k$.
Mizutani, Ryuhei
core +1 more source
On the Initial Set of Constraints for Graph-Based Submodular Function Maximization
Acta CyberneticaA crucial problem in combinatorial optimization is the submodular function maximization (SFM), and in many cases it involves graphs on which the maximization is specified. The problem is well-studied and hence there are several proposed algorithms in the literature.
Eszter Csókás, Tamás Vinkó
openaire +1 more source
Submodular Function Maximization for Group Elevator Scheduling
, 2017 We propose a novel approach for group elevator scheduling by formulating it as the maximization of submodular function under a matroid constraint. In particular, we propose to model the total waiting time of passengers using a quadratic Boolean function.
Raghunathan, Arvind +2 more
core +1 more source
On Equivalence of M$^\natural$-concavity of a Set Function and Submodularity of Its Conjugate
, 2017 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.
Kazuo Murota, Akiyoshi Shioura
openaire +2 more sources
Distributed Submodular Minimization And Motion Coordination Over Discrete State Space
, 2017 Submodular set-functions are extensively used in large-scale combinatorial optimization problems arising in complex networks and machine learning. While there has been significant interest in distributed formulations of convex optimization, distributed ...
Shamma, Jeff S., Jaleel, Hassan
core
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection
, 2022 Submodular functions and variants, through their ability to characterize diversity and coverage, have emerged as a key tool for data selection and summarization. Many recent approaches to learn submodular functions suffer from limited expressiveness.
De, Abir, Chakrabarti, Soumen
core