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Kernel Penalized K-means: A feature selection method based on Kernel K-means
(Elsevier, 2015)
We present an unsupervised method that selects the most relevant features using an embedded strategy while maintaining the cluster structure found with the initial feature set. It is based on the idea of simultaneously ...
Soft clustering - fuzzy and rough approaches and their extensions and derivatives
(Elsevier, 2013)
Clustering is one of the most widely used approaches in data mining with real life
applications in virtually any domain. The huge interest in clustering has led to a possibly
three-digit number of algorithms with the ...
Mean-variance portfolio selection with the ordered weighted average
(IEEE, 2017)
Portfolio selection is the theory that studies the pro-cess of selecting the optimal proportion of different assets. The firstapproach was introduced by Harry Markowitz and was based ona mean-variance framework. This paper ...
Convergence to the Mean Field Game Limit: A Case Study
(Inst Mathematical Statistics, 2020)
We study the convergence of Nash equilibria in a game of optimal stopping. If the associated mean field game has a unique equilibrium, any sequence of n-player equilibria converges to it as n -> infinity. However, both the ...
Mean dimension and an embedding theorem for real flows
(Institute of Mathematics of the Polish Academy of Sciences (IMPAN), 2020)
We develop mean dimension theory for R-flows. We obtain fundamental properties and examples and prove an embedding theorem: Any real flow (X, R) of mean dimension strictly less than r admits an extension (Y, R) whose mean ...
Political risks of recovering and discovering meanings in the collective memory of a perverse religious organisation
(Phoenix, 2020)
This article refers to the political risks that a group of five parishioners, members of an aristocratic Catholic parish located in Santiago, Chile, had to face when they recovered and discovered unconscious meanings about ...
Covariances with OWA operators and Bonferroni means
(Springer, 2020)
The covariance is a statistical technique that is widely used to measure the dispersion between two sets of elements. This work develops new covariance measures by using the ordered weighted average (OWA) operator and ...
About the uniqueness of conformal metrics with pre scribed scalar and mean curvatures on compact manifolds with boundary.
(2011-10-14)
Let (Mⁿ, g) be an n – dimensional compact Riemannian manifold with boundary with n ≥ 2.
In this paper we study the uniquensess of metrics in the conformal class of the metric g having the same scalar curvature in M, aM, ...
Finite topology self-translating surfaces for the mean curvature flow in R3
(Elsevier, 2017)
Finite topology self-translating surfaces for the mean curva-ture flow constitute a key element in the analysis of TypeII singularities from a compact surface because they arise as lim-its after suitable blow-up scalings ...
The Nemytskii operator on bounded p-variation in the mean spaces.
(2012-11-08)
We introduce the notion of bounded p-variation in the sense of [L.sub.p]-norm. We obtain a Riesz type
result for functions of bounded p-variation in the mean. We show that if the Nemytskii operator
map the bounded ...