Zobrazeno 1 - 10
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pro vyhledávání: '"Costarelli, A."'
Autor:
Angeloni, Laura, Bloisi, Domenico Daniele, Burghignoli, Paolo, Comite, Davide, Costarelli, Danilo, Piconi, Michele, Sambucini, Anna Rita, Troiani, Alessio, Veneri, Alessandro
Human actions have accelerated changes in global temperature, precipitation patterns, and other critical Earth systems. Key markers of these changes can be linked to the dynamic of Essential Climate Variables (ECVs) and related quantities, such as So
Externí odkaz:
http://arxiv.org/abs/2412.03523
Autor:
Costarelli, Danilo, Piconi, Michele
In this paper, we provide two algorithms based on the theory of multidimensional neural network (NN) operators activated by hyperbolic tangent sigmoidal functions. Theoretical results are recalled to justify the performance of the here implemented al
Externí odkaz:
http://arxiv.org/abs/2412.00375
In this paper, we introduce the nonlinear exponential Kantorovich sampling series. We establish pointwise and uniform convergence properties and a nonlinear asymptotic formula of the Voronovskaja-type given in terms of the limsup. Furthermore, we ext
Externí odkaz:
http://arxiv.org/abs/2411.15475
As Large Language Models (LLMs) become increasingly integrated into our daily lives, the potential harms from deceptive behavior underlie the need for faithfully interpreting their decision-making. While traditional probing methods have shown some ef
Externí odkaz:
http://arxiv.org/abs/2410.02472
Autor:
Cantarini, Marco, Costarelli, Danilo
In this paper, we considered the problem of the simultaneous approximation of a function and its derivatives by means of the well-known neural network (NN) operators activated by sigmoidal function. Other than a uniform convergence theorem for the de
Externí odkaz:
http://arxiv.org/abs/2409.14189
Autor:
Costarelli, Anthony, Allen, Mat, Hauksson, Roman, Sodunke, Grace, Hariharan, Suhas, Cheng, Carlson, Li, Wenjie, Clymer, Joshua, Yadav, Arjun
Large language models have demonstrated remarkable few-shot performance on many natural language understanding tasks. Despite several demonstrations of using large language models in complex, strategic scenarios, there lacks a comprehensive framework
Externí odkaz:
http://arxiv.org/abs/2406.06613
In this paper we introduce a new family of Bernstein-type exponential polynomials on the hypercube $[0, 1]^d$ and study their approximation properties. Such operators fix a multidimensional version of the exponential function and its square. In parti
Externí odkaz:
http://arxiv.org/abs/2405.16935
Publikováno v:
Constructive Mathematical Analysis, 2024, 7 (2) , 45-68
The aim of this paper is to present a comparison among the fuzzy-type algorithm for image rescaling introduced by Jurio et al., 2011, quoted in the list of references, with some other existing algorithms such as the classical bicubic algorithm and th
Externí odkaz:
http://arxiv.org/abs/2311.14545
Autor:
Michalis, Athanasios, Panagiotakos, Demosthenes B., Papadopoulos, Apostolos, Costarelli, Vassiliki
Publikováno v:
International Journal of Migration, Health and Social Care, 2023, Vol. 20, Issue 3, pp. 369-390.
In this paper, we study the order of approximation for max-product Kantorovich sampling operators based upon generalized kernels in the setting of Orlicz spaces. We establish a quantitative estimate for the considered family of sampling-type operator
Externí odkaz:
http://arxiv.org/abs/2306.03560