284 research outputs found
A new Lenstra-type Algorithm for Quasiconvex Polynomial Integer Minimization with Complexity 2^O(n log n)
We study the integer minimization of a quasiconvex polynomial with
quasiconvex polynomial constraints. We propose a new algorithm that is an
improvement upon the best known algorithm due to Heinz (Journal of Complexity,
2005). This improvement is achieved by applying a new modern Lenstra-type
algorithm, finding optimal ellipsoid roundings, and considering sparse
encodings of polynomials. For the bounded case, our algorithm attains a
time-complexity of s (r l M d)^{O(1)} 2^{2n log_2(n) + O(n)} when M is a bound
on the number of monomials in each polynomial and r is the binary encoding
length of a bound on the feasible region. In the general case, s l^{O(1)}
d^{O(n)} 2^{2n log_2(n) +O(n)}. In each we assume d>= 2 is a bound on the total
degree of the polynomials and l bounds the maximum binary encoding size of the
input.Comment: 28 pages, 10 figure
Using Underapproximations for Sparse Nonnegative Matrix Factorization
Nonnegative Matrix Factorization consists in (approximately) factorizing a
nonnegative data matrix by the product of two low-rank nonnegative matrices. It
has been successfully applied as a data analysis technique in numerous domains,
e.g., text mining, image processing, microarray data analysis, collaborative
filtering, etc.
We introduce a novel approach to solve NMF problems, based on the use of an
underapproximation technique, and show its effectiveness to obtain sparse
solutions. This approach, based on Lagrangian relaxation, allows the resolution
of NMF problems in a recursive fashion. We also prove that the
underapproximation problem is NP-hard for any fixed factorization rank, using a
reduction of the maximum edge biclique problem in bipartite graphs.
We test two variants of our underapproximation approach on several standard
image datasets and show that they provide sparse part-based representations
with low reconstruction error. Our results are comparable and sometimes
superior to those obtained by two standard Sparse Nonnegative Matrix
Factorization techniques.Comment: Version 2 removed the section about convex reformulations, which was
not central to the development of our main results; added material to the
introduction; added a review of previous related work (section 2.3);
completely rewritten the last part (section 4) to provide extensive numerical
results supporting our claims. Accepted in J. of Pattern Recognitio
New approximations for the cone of copositive matrices and its dual
We provide convergent hierarchies for the cone C of copositive matrices and
its dual, the cone of completely positive matrices. In both cases the
corresponding hierarchy consists of nested spectrahedra and provide outer
(resp. inner) approximations for C (resp. for its dual), thus complementing
previous inner (resp. outer) approximations for C (for the dual). In
particular, both inner and outer approximations have a very simple
interpretation. Finally, extension to K-copositivity and K-complete positivity
for a closed convex cone K, is straightforward.Comment: 8
The strong thirteen spheres problem
The thirteen spheres problem is asking if 13 equal size nonoverlapping
spheres in three dimensions can touch another sphere of the same size. This
problem was the subject of the famous discussion between Isaac Newton and David
Gregory in 1694. The problem was solved by Schutte and van der Waerden only in
1953.
A natural extension of this problem is the strong thirteen spheres problem
(or the Tammes problem for 13 points) which asks to find an arrangement and the
maximum radius of 13 equal size nonoverlapping spheres touching the unit
sphere. In the paper we give a solution of this long-standing open problem in
geometry. Our computer-assisted proof is based on a enumeration of the
so-called irreducible graphs.Comment: Modified lemma 2, 16 pages, 12 figures. Uploaded program packag
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