We conduct a comprehensive review on multi-level facility location problems which extend
several classical facility location problems and can be regarded as a subclass within the …

Submodularity1 is a property of set functions with deep theoretical consequences and far–
reaching applications. At first glance it appears very similar to concavity, in other ways it …

We consider the\sf Unconstrained Submodular Maximization problem in which we are given
a nonnegative submodular function f:2^N→R^+, and the objective is to find a subset S⊆N …

Let f:2^X→\calR_+ be a monotone submodular set function, and let (X,\calI) be a matroid.
We consider the problem \rmmax_S∈\calIf(S). It is known that the greedy algorithm yields a …

The α-expansion algorithm has had a significant impact in computer vision due to its
generality, effectiveness, and speed. It is commonly used to minimize energies that involve …

There has been much progress recently on improved approximations for problems involving
submodular objective functions, and many interesting techniques have been developed …

Submodular maximization generalizes many important problems including Max Cut in
directed and undirected graphs and hypergraphs, certain constraint satisfaction problems …

We consider the problem of maximizing a non-negative submodular set function f: 2N-> RR+
over a ground set N subject to a variety of packing type constraints including (multiple) …

We investigate two new optimization problems—minimizing a submodular function subject
to a submodular lower bound constraint (submodular cover) and maximizing a submodular …

Many large-scale machine learning problems (such as clustering, non-parametric learning,
kernel machines, etc.) require selecting, out of a massive data set, a manageable …