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Graphs and Combinatorics, 2001
Let \(S\) be a quasiordered set (quoset) or topological space and \(\text{Sub} S\) be the set of all nonempty subquosets or subspaces quasiordered by embeddability, respectively. For a cardinal number \(n\), \(p_n\) and \(q_n\) denote the smallest size of spaces \(S\) such that each poset respectively quoset with \(n\) points is embeddable in \(\text ...
Erné, Marcel, Reinhold, Jürgen
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Let \(S\) be a quasiordered set (quoset) or topological space and \(\text{Sub} S\) be the set of all nonempty subquosets or subspaces quasiordered by embeddability, respectively. For a cardinal number \(n\), \(p_n\) and \(q_n\) denote the smallest size of spaces \(S\) such that each poset respectively quoset with \(n\) points is embeddable in \(\text ...
Erné, Marcel, Reinhold, Jürgen
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Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017
Network embedding is increasingly employed to assist network analysis as it is effective to learn latent features that encode linkage information. Various network embedding methods have been proposed, but they are only designed for a single network scenario.
Linchuan Xu +3 more
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Network embedding is increasingly employed to assist network analysis as it is effective to learn latent features that encode linkage information. Various network embedding methods have been proposed, but they are only designed for a single network scenario.
Linchuan Xu +3 more
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Journal of the American Statistical Association, 2020
Numerical embedding has become one standard technique for processing and analyzing unstructured data that cannot be expressed in a predefined fashion. It stores the main characteristics of data by mapping it onto a numerical vector. An embedding is often unsupervised and constructed by transfer learning from large-scale unannotated data.
Ben, Dai, Xiaotong, Shen, Junhui, Wang
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Numerical embedding has become one standard technique for processing and analyzing unstructured data that cannot be expressed in a predefined fashion. It stores the main characteristics of data by mapping it onto a numerical vector. An embedding is often unsupervised and constructed by transfer learning from large-scale unannotated data.
Ben, Dai, Xiaotong, Shen, Junhui, Wang
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Embedded Links, Embedded Meanings
Journalism Studies, 2016Social media transform the consumption environment of news by allowing users to separate individual stories from their original context within a bounded news product and recirculate them in new contexts. If, as this essay argues, the meaning of a news story stems from the interplay of textual and contextual elements, then this shift has interpretive ...
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Evolutionary Computation, 2002
In this paper we introduce embedded landscapes as an extension of NK landscapes and MAXSAT problems. This extension is valid for problems where the representation can be expressed as a simple sum of subfunctions over subsets of the representation domain.
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In this paper we introduce embedded landscapes as an extension of NK landscapes and MAXSAT problems. This extension is valid for problems where the representation can be expressed as a simple sum of subfunctions over subsets of the representation domain.
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2001
Model checking would answer all finite-state verification problems, if it were not for the notorious state-space explosion problem. A problem of practical importance, which attracted less attention, is to close open systems. Standard model checkers cannot handle open systems directly and closing is commonly done by adding an environment process, which ...
Sidorova, N., Steffen, M.
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Model checking would answer all finite-state verification problems, if it were not for the notorious state-space explosion problem. A problem of practical importance, which attracted less attention, is to close open systems. Standard model checkers cannot handle open systems directly and closing is commonly done by adding an environment process, which ...
Sidorova, N., Steffen, M.
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2008
Embedded methods are a relatively new approach to feature selection. Unlike filter methods, which do not incorporate learning, and wrapper approaches, which can be used with arbitrary classifiers, in embedded methods the features selection part can not be separated from the learning part.
Lal, T. +3 more
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Embedded methods are a relatively new approach to feature selection. Unlike filter methods, which do not incorporate learning, and wrapper approaches, which can be used with arbitrary classifiers, in embedded methods the features selection part can not be separated from the learning part.
Lal, T. +3 more
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Journal of Symbolic Logic, 1969
Since Cohen [1] showed the independence of the axiom of choice from the other axioms of ZF, a number of people have used his forcing technique to show how badly choice can fail while certain vestiges of it remain. Many of these arguments involve the introduction of a generic sequence or generic set of generic sets of ordinals into a countable standard ...
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Since Cohen [1] showed the independence of the axiom of choice from the other axioms of ZF, a number of people have used his forcing technique to show how badly choice can fail while certain vestiges of it remain. Many of these arguments involve the introduction of a generic sequence or generic set of generic sets of ordinals into a countable standard ...
openaire +1 more source