Results 141 to 150 of about 517 (178)

Interpretable nonconvex submodule clustering algorithm using ℓr-induced tensor nuclear norm and ℓ2,p column sparse norm with global convergence guarantees. [PDF]

PLoS One
Yang M, Han S, Chen L, Wang J.
europepmc   +1 more source

The cyclic flats of a q-matroid. [PDF]

J Algebr Comb (Dordr)
Alfarano GN, Byrne E.
europepmc   +1 more source

Submodular function minimization and polarity [PDF]

Mathematical Programming, 2021
Using polarity, we give an outer polyhedral approximation for the epigraph of set functions. For a submodular function, we prove that the corresponding polar relaxation is exact; hence, it is equivalent to the Lovász extension. The polar approach provides an alternative proof for the convex hull description of the epigraph of a submodular function ...
Alper Atamtürk, Atamtürk Alper, Vishnu Narayanan   +2 more
exaly   +3 more sources

Some of the next articles are maybe not open access.

Related searches:

Submodular function minimization

Mathematical Programming, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Satoru Iwata, Iwata Satoru
exaly   +2 more sources

Submodular Functions and Rooted Trees

Theory of Computing Systems, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yaokun Wu, Yinfeng Zhu 0001
openaire   +1 more source

Decomposition of submodular functions

Combinatorica, 1983
A decomposition theory for submodular functions is described. Any such function is shown to have a unique decomposition consisting of indecomposable functions and certain highly decomposable functions, and the latter are completely characterized. Applications include decompositions of hypergraphs based on edge and vertex connectivity, the decomposition
openaire   +1 more source

On submodular function minimization

Combinatorica, 1985
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

On the subdifferential of a submodular function

Mathematical Programming, 1984
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Submodular functions and convexity

1983
In “continuous” optimization convex functions play a central role. Besides elementary tools like differentiation, various methods for finding the minimum of a convex function constitute the main body of nonlinear optimization. But even linear programming may be viewed as the optimization of very special (linear) objective functions over very special ...
openaire   +1 more source