DR-submodular functions encompass a broad class of functions which are generally non-convex and non-concave. We study the problem of minimizing any DR-submodular function, with continuous and general integer variables, under box constraints and possibly additional monotonicity constraints. We propose valid linear inequalities for the epigraph of any DR-submodular function under the constraints. We further provide the complete convex hull of such an epigraph, which, surprisingly, turns out to be polyhedral. We propose a polynomial-time exact separation algorithm for our proposed valid inequalities, with which we first establish the polynomial-time solvability of this class of mixed-integer nonlinear optimization problems
Many combinatorial problems arising in machine learning can be reduced to the problem of minimizing ...
We consider non-monotone DR-submodular function maximization, where DR-submodularity (diminishing re...
The connections between convexity and submodularity are explored, for purposes of minimizing and lea...
We study the polyhedral convex hull structure of a mixed-integer set which arises in a class of card...
Various kinds of optimization problems involve nonlinear functions of binary variables that exhibit ...
International audienceMany real-world problems can often be cast as the optimization of DR-submodula...
International audienceSubmodular set-functions have many applications in combinatorial optimization,...
In this paper, we study fundamental problems of maximizing DR-submodular continuous functions that h...
International audienceIn this paper, we study fundamental problems of maximizing DR-submodular conti...
Submodular maximization under various constraints is a fundamental problem studied continuously, in ...
Continuous DR-submodular functions are a class of functions that satisfy the Diminishing Returns (DR...
Set-functions appear in many areas of computer science and applied mathematics, such as machine lear...
Continuous submodular functions are a category of generally non-convex/non-concave functions with a ...
International audienceSubmodular functions are relevant to machine learning for at least two reasons...
Many combinatorial problems arising in machine learning can be reduced to the problem of minimizing ...
Many combinatorial problems arising in machine learning can be reduced to the problem of minimizing ...
We consider non-monotone DR-submodular function maximization, where DR-submodularity (diminishing re...
The connections between convexity and submodularity are explored, for purposes of minimizing and lea...
We study the polyhedral convex hull structure of a mixed-integer set which arises in a class of card...
Various kinds of optimization problems involve nonlinear functions of binary variables that exhibit ...
International audienceMany real-world problems can often be cast as the optimization of DR-submodula...
International audienceSubmodular set-functions have many applications in combinatorial optimization,...
In this paper, we study fundamental problems of maximizing DR-submodular continuous functions that h...
International audienceIn this paper, we study fundamental problems of maximizing DR-submodular conti...
Submodular maximization under various constraints is a fundamental problem studied continuously, in ...
Continuous DR-submodular functions are a class of functions that satisfy the Diminishing Returns (DR...
Set-functions appear in many areas of computer science and applied mathematics, such as machine lear...
Continuous submodular functions are a category of generally non-convex/non-concave functions with a ...
International audienceSubmodular functions are relevant to machine learning for at least two reasons...
Many combinatorial problems arising in machine learning can be reduced to the problem of minimizing ...
Many combinatorial problems arising in machine learning can be reduced to the problem of minimizing ...
We consider non-monotone DR-submodular function maximization, where DR-submodularity (diminishing re...
The connections between convexity and submodularity are explored, for purposes of minimizing and lea...