Zobrazeno 1 - 10
of 43 458
pro vyhledávání: '"Kantorovich A"'
Autor:
VASIAN, BIANCA IOANA1 bianca.vasian@unitbv.r
Publikováno v:
Carpathian Journal of Mathematics. 2024, Vol. 40 Issue 1, p187-194. 8p.
In the current article, we establish a distinct version of the operators defined by Berwal \emph{et al.}, which is the Kantorovich type modification of $\alpha$-Bernstein operators to approximate Lebesgue's integrable functions. We define its modific
Externí odkaz:
http://arxiv.org/abs/2409.17594
We consider the problem of finding the ``best'' approximation of an $n$-dimensional probability measure $\rho$ using a measure $\nu$ whose support is parametrized by $f : \mathbb{R}^m \to \mathbb{R}^n$ where $m < n$. We quantify the performance of th
Externí odkaz:
http://arxiv.org/abs/2409.16541
Tools from optimal transport (OT) theory have recently been used to define a notion of quantile function for directional data. In practice, regularization is mandatory for applications that require out-of-sample estimates. To this end, we introduce a
Externí odkaz:
http://arxiv.org/abs/2407.02085
Autor:
Hillbrecht, Sebastian
As the title suggests, this is the third paper in a series addressing bilevel optimization problems that are governed by the Kantorovich problem of optimal transport. These tasks can be reformulated as mathematical problems with complementarity const
Externí odkaz:
http://arxiv.org/abs/2406.08992
In this work, we study the Kantorovich variant of max-min neural network operators, in which the operator kernel is defined in terms of sigmoidal functions. Our main aim is to demonstrate the $L^{p}$-convergence of these nonlinear operators for $1\le
Externí odkaz:
http://arxiv.org/abs/2407.03329
Autor:
Zhang, Yunzhi1 (AUTHOR) zyz@jsut.edu.cn, Guo, Xiaotian1 (AUTHOR), Liu, Jianzhong1 (AUTHOR), Chen, Xueping1 (AUTHOR) chenxueping@jsut.edu.cn
Publikováno v:
Mathematics (2227-7390). Sep2024, Vol. 12 Issue 18, p2860. 13p.
We extend the notion of Cantor-Kantorovich distance between Markov chains introduced by (Banse et al., 2023) in the context of Markov Decision Processes (MDPs). The proposed metric is well-defined and can be efficiently approximated given a finite ho
Externí odkaz:
http://arxiv.org/abs/2407.08324
Autor:
Emami, Pedram, Pass, Brendan
We consider the Monge-Kantorovich problem between two random measuress. More precisely, given probability measures $\mathbb{P}_1,\mathbb{P}_2\in\mathcal{P}(\mathcal{P}(M))$ on the space $\mathcal{P}(M)$ of probability measures on a smooth compact man
Externí odkaz:
http://arxiv.org/abs/2406.08585
Abstractions of dynamical systems enable their verification and the design of feedback controllers using simpler, usually discrete, models. In this paper, we propose a data-driven abstraction mechanism based on a novel metric between Markov models. O
Externí odkaz:
http://arxiv.org/abs/2405.08353