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- W2551539964 abstract "Fundamental challenges and goals of the cognitive algorithms are moving super-intelligent machines and super-intelligent humans from dreams to reality. This paper is devoted to a technical way to reach some specific aspects of super-intelligence that are beyond the current human cognitive abilities. Specifically the proposed technique is to overcome inabilities to analyze a large amount of abstract numeric high-dimensional data and finding complex patterns in these data with a naked eye. Discovering patterns in multidimensional data using visual means is a long-standing problem in multiple fields and Data Science and Modeling in general. The major challenge is that we cannot see n-D data by a naked eye and need visualization tools to represent n-D data in 2-D losslessly. The number of available lossless methods is quite limited. The objective of this paper is expanding the class of such lossless methods, by proposing a new concept of Generalized Shifted Collocated Paired Coordinates. The paper shows the advantages of proposed lossless technique by proving mathematical properties and by demonstration on real data." @default.
- W2551539964 created "2016-11-30" @default.
- W2551539964 creator A5089775223 @default.
- W2551539964 date "2016-07-01" @default.
- W2551539964 modified "2023-09-23" @default.
- W2551539964 title "Super-intelligence challenges and lossless visual representation of high-dimensional data" @default.
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- W2551539964 doi "https://doi.org/10.1109/ijcnn.2016.7727418" @default.
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