Abstract. Domain decomposition is a well known technique in parallel computing. It requires the decomposition of a problem domain into sub-domains.
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Nov 14, 2022 · Abstract:Saliency methods attempt to explain deep neural networks by highlighting the most salient features of a sample.
Mar 4, 2024 · Module decomposition is a process in system design and architecture where a complex system is broken down into smaller, more manageable modules or components.
This example points out that a bottom-up approach can contribute to creating a design that has a rigorous top-down decomposition. *. Pro: Creates a clean ...
A 'Decomposition Pattern' in Computer Science refers to a specific way of breaking down a problem or task into smaller parts.
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We present a novel data mining approach basedon decomposition. In order to analyze a givendataset, the method decomposes it to a hierarchyof smaller and ...
This paper describes a taxonomy of decomposition strategies based on the design attributes of structures, behaviors, and goals.
Abstract. Selecting a minimal feature set that is maximally informative about a target variable is a central task in machine learning and statistics.
Functional decomposition refers broadly to the process of resolving a functional relationship into its constituent parts in such a way that the original ...
Jan 31, 2023 · Signal decomposition (SD) approaches aim to decompose non-stationary signals into their constituent amplitude- and frequency-modulated components.