Despite the rich existing literature about minimax optimization in conti...
In recent years, maximization of DR-submodular continuous functions beca...
Despite a surge of interest in submodular maximization in the data strea...
Motivated by practical applications, recent works have considered
maximi...
Over the last two decades, submodular function maximization has been the...
The problem of finding a maximum size matching in a graph (known as the
...
Recent progress in (semi-)streaming algorithms for monotone submodular
f...
It has been well established that first order optimization methods can
c...
We propose subsampling as a unified algorithmic technique for submodular...
In this paper, we present SimultaneousGreedys, a deterministic algorithm...
In this paper, we propose the first continuous optimization algorithms t...
We consider the classical problem of maximizing a monotone submodular
fu...
In this paper, we propose scalable methods for maximizing a regularized
...
In this paper, we propose a novel framework that converts streaming
algo...
In this paper we consider the problem of maximizing a non-negative submo...
In this paper we consider the problem of finding a maximum weight set su...
It is generally believed that submodular functions -- and the more gener...
In many machine learning applications, one needs to interactively select...
In this paper, we consider the unconstrained submodular maximization pro...
We consider the problem of maximizing the sum of a monotone submodular
f...
We study the problem of maximizing a monotone submodular function subjec...
The Submodular Welfare Maximization problem (SWM) captures an important
...
In a nutshell, submodular functions encode an intuitive notion of dimini...
In this paper, we develop the first one-pass streaming algorithm for
sub...
Submodular functions are a broad class of set functions, which naturally...
In many machine learning applications, it is important to explain the
pr...