Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Vandaele, Arnaud"'
Boolean matrix factorization (BMF) approximates a given binary input matrix as the product of two smaller binary factors. As opposed to binary matrix factorization which uses standard arithmetic, BMF uses the Boolean OR and Boolean AND operations to
Externí odkaz:
http://arxiv.org/abs/2305.10185
In this paper, we study the following nonlinear matrix decomposition (NMD) problem: given a sparse nonnegative matrix $X$, find a low-rank matrix $\Theta$ such that $X \approx f(\Theta)$, where $f$ is an element-wise nonlinear function. We focus on t
Externí odkaz:
http://arxiv.org/abs/2305.08687
Publikováno v:
Machine Learning 111, pp. 4453-4495, 2022
Nonnegative least squares problems with multiple right-hand sides (MNNLS) arise in models that rely on additive linear combinations. In particular, they are at the core of most nonnegative matrix factorization algorithms and have many applications. T
Externí odkaz:
http://arxiv.org/abs/2011.11066
We propose a new variant of nonnegative matrix factorization (NMF), combining separability and sparsity assumptions. Separability requires that the columns of the first NMF factor are equal to columns of the input matrix, while sparsity requires that
Externí odkaz:
http://arxiv.org/abs/2006.07553
Symmetric nonnegative matrix factorization (symNMF) is a variant of nonnegative matrix factorization (NMF) that allows to handle symmetric input matrices and has been shown to be particularly well suited for clustering tasks. In this paper, we presen
Externí odkaz:
http://arxiv.org/abs/2003.04775
Publikováno v:
IEEE Signal Processing Letters 27 (1), pp. 81-85, 2020
Nonnegative matrix factorization (NMF) is a widely used linear dimensionality reduction technique for nonnegative data. NMF requires that each data point is approximated by a convex combination of basis elements. Archetypal analysis (AA), also referr
Externí odkaz:
http://arxiv.org/abs/1910.00821
Publikováno v:
Computational Optimization and Applications 71 (1), pp. 193-219, 2018
This paper considers the problem of positive semidefinite factorization (PSD factorization), a generalization of exact nonnegative matrix factorization. Given an $m$-by-$n$ nonnegative matrix $X$ and an integer $k$, the PSD factorization problem cons
Externí odkaz:
http://arxiv.org/abs/1707.07953
Publikováno v:
IEEE Transactions on Signal Processing 64 (21), pp. 5571-5584, 2016
Given a symmetric nonnegative matrix $A$, symmetric nonnegative matrix factorization (symNMF) is the problem of finding a nonnegative matrix $H$, usually with much fewer columns than $A$, such that $A \approx HH^T$. SymNMF can be used for data analys
Externí odkaz:
http://arxiv.org/abs/1509.01404
Publikováno v:
Linear Algebra and its Applications 521, pp. 217-239, 2017
In this paper, we propose new lower and upper bounds on the linear extension complexity of regular $n$-gons. Our bounds are based on the equivalence between the computation of (i) an extended formulation of size $r$ of a polytope $P$, and (ii) a rank
Externí odkaz:
http://arxiv.org/abs/1505.08031
Publikováno v:
Journal of Global Optimization 65 (2), pp 369-400, 2016
The exact nonnegative matrix factorization (exact NMF) problem is the following: given an $m$-by-$n$ nonnegative matrix $X$ and a factorization rank $r$, find, if possible, an $m$-by-$r$ nonnegative matrix $W$ and an $r$-by-$n$ nonnegative matrix $H$
Externí odkaz:
http://arxiv.org/abs/1411.7245