Sign Up to like & get
recommendations!
0
Published in 2019 at "Periodica Mathematica Hungarica"
DOI: 10.1007/s10998-018-0260-1
Abstract: In this paper we will study k-commuting mappings of generalized matrix algebras. The general form of arbitrary k-commuting mapping of a generalized matrix algebra is determined. It is shown that under mild assumptions, every k-commuting…
read more here.
Keywords:
matrix algebras;
algebra;
mappings generalized;
generalized matrix ... See more keywords
Sign Up to like & get
recommendations!
0
Published in 2020 at "IEEE Intelligent Systems"
DOI: 10.1109/mis.2020.3036136
Abstract: Learning effective representations of users and items is crucially important to recommendation with implicit feedback. Matrix factorization is the basic idea to derive the representations of users and items by decomposing the given interaction matrix.…
read more here.
Keywords:
matrix;
generalized matrix;
matrix factorization;
implicit feedback ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2017 at "Mathematica Slovaca"
DOI: 10.1515/ms-2017-0021
Abstract: Abstract We introduce a convergence of weight g: ℕ → [0, ∞) where g(n) → ∞ and n/g(n) ↛ 0 with respect to a summability matrix method A for sequences (which generalizes the notion of…
read more here.
Keywords:
certain generalized;
matrix;
matrix methods;
generalized matrix ... See more keywords
Sign Up to like & get
recommendations!
1
Published in 2018 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2018.00115
Abstract: Emerging neural hardware substrates, such as IBM's TrueNorth Neurosynaptic System, can provide an appealing platform for deploying numerical algorithms. For example, a recurrent Hopfield neural network can be used to find the Moore-Penrose generalized inverse…
read more here.
Keywords:
matrix inverse;
generalized matrix;
inverse;
ibm truenorth ... See more keywords