Synergy and Redundancy Measures
The following Special Issue covers advances in both the theoretical formulation and applications of information-theoretic measures of synergy and redundancy. An important aspect of how sources of information are distributed across a set of variables concerns whether different variables provide redun...
Wedi'i Gadw mewn:
| Fformat: | Online |
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| Iaith: | Saesneg |
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Pynciau: | |
| Mynediad Ar-lein: | ONIX_20250812T110751_9783725836130_98 |
| Tagiau: |
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
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| _version_ | 1869521968483532800 |
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| collection | Directory of Open Access Books |
| description | The following Special Issue covers advances in both the theoretical formulation and applications of information-theoretic measures of synergy and redundancy. An important aspect of how sources of information are distributed across a set of variables concerns whether different variables provide redundant, unique, or synergistic information when combined with other variables. Intuitively, variables share redundant information if each variable individually carries the same information carried by other variables. Information carried by a certain variable is unique if it is not carried by any other variables or their combination, and a group of variables carries synergistic information if some information arises only when they are combined. Recent advances have contributed to building an information-theoretic framework to determine the distribution and nature of information extractable from multivariate data sets. Measures of redundant, unique, or synergistic information characterize dependencies between the parts of a multivariate system and can help to understand its function and mechanisms. This Special issue provides updates on advances in the formulation and application of decompositions of the information carried by a set of variables about a target of interest. Advances in the theoretical formulation comprise the connection with channel ordering, with information compression, and the characterization of decision regions. Applications extend to, among others, structure learning, characterizing emergence in complex systems, and understanding representations in cognition. |
| format | Online |
| id | doab-20.500.12854ir-165342 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1653422025-08-12T09:22:46Z Synergy and Redundancy Measures Chicharro, Daniel partial information decomposition redundancy synergy information flow analysis tropical probability entropic cone information theory union information communication channels f-information Rényi-information causality directed acyclic graphs causal discovery structure learning causal structures marginal scenarios hidden variables mutual information unique information entropic inequalities data processing inequality information bottleneck rate distortion affordances direct perception ecological information emergence information diagrams decomposition comparison of channels Blackwell order information-theoretic cryptography secret key rate secrecy monotones Le Cam deficiency resource theories thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries The following Special Issue covers advances in both the theoretical formulation and applications of information-theoretic measures of synergy and redundancy. An important aspect of how sources of information are distributed across a set of variables concerns whether different variables provide redundant, unique, or synergistic information when combined with other variables. Intuitively, variables share redundant information if each variable individually carries the same information carried by other variables. Information carried by a certain variable is unique if it is not carried by any other variables or their combination, and a group of variables carries synergistic information if some information arises only when they are combined. Recent advances have contributed to building an information-theoretic framework to determine the distribution and nature of information extractable from multivariate data sets. Measures of redundant, unique, or synergistic information characterize dependencies between the parts of a multivariate system and can help to understand its function and mechanisms. This Special issue provides updates on advances in the formulation and application of decompositions of the information carried by a set of variables about a target of interest. Advances in the theoretical formulation comprise the connection with channel ordering, with information compression, and the characterization of decision regions. Applications extend to, among others, structure learning, characterizing emergence in complex systems, and understanding representations in cognition. 2025-08-12T09:22:44Z 2025-08-12T09:22:44Z 2025 book ONIX_20250812T110751_9783725836130_98 9783725836130 9783725836147 https://directory.doabooks.org/handle/20.500.12854/165342 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10761 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-3614-7 10.3390/books978-3-7258-3614-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725836130 9783725836147 284 open access |
| spellingShingle | partial information decomposition redundancy synergy information flow analysis tropical probability entropic cone information theory union information communication channels f-information Rényi-information causality directed acyclic graphs causal discovery structure learning causal structures marginal scenarios hidden variables mutual information unique information entropic inequalities data processing inequality information bottleneck rate distortion affordances direct perception ecological information emergence information diagrams decomposition comparison of channels Blackwell order information-theoretic cryptography secret key rate secrecy monotones Le Cam deficiency resource theories thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Synergy and Redundancy Measures |
| title | Synergy and Redundancy Measures |
| title_full | Synergy and Redundancy Measures |
| title_fullStr | Synergy and Redundancy Measures |
| title_full_unstemmed | Synergy and Redundancy Measures |
| title_short | Synergy and Redundancy Measures |
| title_sort | synergy and redundancy measures |
| topic | partial information decomposition redundancy synergy information flow analysis tropical probability entropic cone information theory union information communication channels f-information Rényi-information causality directed acyclic graphs causal discovery structure learning causal structures marginal scenarios hidden variables mutual information unique information entropic inequalities data processing inequality information bottleneck rate distortion affordances direct perception ecological information emergence information diagrams decomposition comparison of channels Blackwell order information-theoretic cryptography secret key rate secrecy monotones Le Cam deficiency resource theories thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | partial information decomposition redundancy synergy information flow analysis tropical probability entropic cone information theory union information communication channels f-information Rényi-information causality directed acyclic graphs causal discovery structure learning causal structures marginal scenarios hidden variables mutual information unique information entropic inequalities data processing inequality information bottleneck rate distortion affordances direct perception ecological information emergence information diagrams decomposition comparison of channels Blackwell order information-theoretic cryptography secret key rate secrecy monotones Le Cam deficiency resource theories thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20250812T110751_9783725836130_98 |