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Product Convolution of Generalized Subexponential Distributions
Mathematics, 2023 Assume that ξ and η are two independent random variables with distribution functions Fξ and Fη, respectively. The distribution of a random variable ξη, denoted by Fξ⊗Fη, is called the product-convolution of Fξ and Fη.
Gustas Mikutavičius, Jonas Šiaulys
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A note on product-convolution for generalized subexponential distributions
Nonlinear Analysis, 2022 In this paper, we consider the stability property of the class of generalized subexponential distributions with respect to product-convolution. Assuming that the primary distribution is in the class of generalized subexponential distributions, we find ...
Dimitrios Konstantinides +2 more
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A New Support Vector Machine Based on Convolution Product
Complexity, 2021 The support vector machine (SVM) and deep learning (e.g., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. Nonetheless, smaller datasets may be very important, costly, and not easy to obtain in
Wei-Chang Yeh +3 more
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Convolution Product for Hilbert $C^*$-Module Valued Maps [PDF]
Sahand Communications in Mathematical Analysis, 2023 In this paper, we introduce a convolution-type product for strongly integrable Hilbert $C^*$-module valued maps on locally compact groups. We investigate various properties of this product related to uniform continuity, boundless, etc.
Mawoussi Todjro, Yaogan Mensah
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The quantum convolution product
Journal of Physics: Conference SeriesIn classical statistical mechanics, physical states (probability measures) are embedded in the Banach algebra of complex Borel measures on phase space, where the algebra product is realized by convolution.
P. Aniello
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Abstract and Applied Analysis, 2010 We define the so-called box convolution product and study their properties in order to present the approximate solutions for the general coupled matrix convolution equations by using iterative methods.
Adem Kılıçman, Zeyad Al zhour
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Modeling User Behavior with Graph Convolution for Personalized Product Search [PDF]
The Web Conference, 2022 User preference modeling is a vital yet challenging problem in personalized product search. In recent years, latent space based methods have achieved state-of-the-art performance by jointly learning semantic representations of products, users, and text ...
Fan Lu +9 more
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Homotopy Invariance of Convolution Products [PDF]
International Mathematics Research Notices, 2020 AbstractThe purpose of this paper is to show that various convolution products are fully homotopical, meaning that they preserve weak equivalences in both variables without any cofibrancy hypothesis. We establish this property for diagrams of simplicial sets indexed by the category of finite sets and injections and for tame $M$-simplicial sets, with $M$
Sagave, S., Sagave, S., Schwede, S.
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Holomorphic Cohomological Convolution and Hadamard Product [PDF]
Publications of the Research Institute for Mathematical Sciences, 2022 In this article we explain the link between Pohlen’s extended Hadamard product and the holomorphic cohomological convolution on \mathbb{C}^* . For this purpose we introduce a generalized Hadamard product, which is defined even if the holomorphic ...
Dubussy, Christophe +1 more
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Mathematics, 2021 Segal introduce the Fourier–Wiener transform for the class of polynomial cylinder functions on Hilbert space, and Hida then develop this concept. Negrin define the extended Wiener transform with Hayker et al. In recent papers, Hayker et al. establish the
Hyun Soo Chung
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