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Aug 1, 2020 · In this work, the major developments in the theory of kernel function approximation are reviewed in a systematic manner and the practical applications are ...
In this regard, kernel function approximation using explicit feature maps have emerged as a substitute for traditional kernel based methods.
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Abstract: Kernel based methods have become popular in a wide variety of machine learning tasks. They rely on the computation of kernel functions, ...
Aug 1, 2020 · Explicit kernel maps have emerged as an alternative to standard kernel functions in order to overcome the latter's scalability issues. An ...
Journal: Artificial Intelligence Review, 2020, № 2, p. 843-876 ; Publisher: Springer Science and Business Media LLC ; Authors: Deena P. Francis, Kumudha Raimond.
Oct 30, 2024 · Over the past decade, significant advances have been made in establishing theoretically grounded algorithms for various settings. In this ...
This review study aims to summarize the most up-to-date cumulative studies on kernel functions, their application categories, and their integration with data- ...
In this paper, given an arbitrary kernel function, we introduce an explicit, finite-dimensional feature map for any arbitrary kernel function that ensures the ...
Mar 11, 2024 · This paper contributes to statistical methods building on reproducing kernel Hilbert spaces. These methods have become popular in ...
Aug 1, 2020 · 主要重点是提高基于内核的方法的可扩展性。在这方面，使用显式特征图的核函数逼近已经成为传统基于核的方法的替代品。多年来，从理论角度来看，显式核映射 ...