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Short answer Check out the paper of Shuman et al. [1], it provides some background on Graph Signal Processing, including answers to your questions in sections II.C and III.A Long Answer Question 1 Yes, the filter $g_{\theta}$ is analogous to CNN's filter. You have a diagonal matrix with $\theta_{i}$ in its diagonal mainly for matrix-multiplication purposes (...


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(Disclaimer: although I have never seen a formal definition of unknown search space, here is my attempt to define it based on my knowledge of search and search algorithms in machine learning and evolutionary algorithms; I am aware of a definition of unknown environment (see chapter 2, p. 44, of Norvig and Russell's AI book), but that definition is different ...


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That term exactly refers to the difference between two main paradigms in probability and statistics: Frequentism vs Bayesianism. You can find many texts for explaining the difference, for example [1] and [2]. By the way, we can briefly say it means that we assume that there exists a fixed opinion out there (like a parameter of a distribution function) and we ...


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You can find a brief explanation of hierarchical feature selection in the following from "An Empirical Evaluation of Hierarchical Feature Selection Methods for Classification in Bioinformatics Datasets with Gene Ontology-based Features" paper: Hierarchical feature selection is a new research area in machine learning/data mining, which consists of ...


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It consists of organizing training in a series of learning problems, each relying on small "support" and "query" sets to mimic the few-shot circumstances encountered during evaluation.(an episode is a single task)


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