Causality, probability, and time
Causality is a key part of many fields and facets of life, from finding the relationship between diet and disease to discovering the reason for a particular stock market crash. Despite centuries of work in philosophy and decades of computational research, automated inference and explanation remains...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
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2013
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| 245 | 1 | 0 | |a Causality, probability, and time |c Samantha Kleinberg, Stevens Institute of Technology, Hoboken, New Jersey |
| 246 | 1 | 3 | |a Causality, Probability, & Time |
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| 300 | |a 1 Online-Ressource (vii, 259 Seiten) | ||
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| 500 | |a Title from publisher's bibliographic system (viewed on 05 Oct 2015) | ||
| 505 | 8 | |a 1. Introduction -- 2. A brief history of causality -- 3. Probability, logic and probabilistic temporal logic -- 4. Defining causality -- 5. Inferring causality -- 6. Token causality -- 7. Case studies -- 8. Conclusion -- Appendix A.A little bit of statistics -- Appendix B. Proofs | |
| 520 | |a Causality is a key part of many fields and facets of life, from finding the relationship between diet and disease to discovering the reason for a particular stock market crash. Despite centuries of work in philosophy and decades of computational research, automated inference and explanation remains an open problem. In particular, the timing and complexity of relationships has been largely ignored even though this information is critically important for prediction, explanation and intervention. However, given the growing availability of large observational datasets including those from electronic health records and social networks, it is a practical necessity. This book presents a new approach to inference (finding relationships from a set of data) and explanation (assessing why a particular event occurred), addressing both the timing and complexity of relationships. The practical use of the method developed is illustrated through theoretical and experimental case studies, demonstrating its feasibility and success | ||
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Datensatz im Suchindex
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|---|---|
| any_adam_object | |
| author | Kleinberg, Samantha 1983- |
| author_GND | (DE-588)1044034181 |
| author_facet | Kleinberg, Samantha 1983- |
| author_role | aut |
| author_sort | Kleinberg, Samantha 1983- |
| author_variant | s k sk |
| building | Verbundindex |
| bvnumber | BV043945585 |
| classification_rvk | CC 2600 CC 4400 ST 130 ST 134 |
| collection | ZDB-20-CBO |
| contents | 1. Introduction -- 2. A brief history of causality -- 3. Probability, logic and probabilistic temporal logic -- 4. Defining causality -- 5. Inferring causality -- 6. Token causality -- 7. Case studies -- 8. Conclusion -- Appendix A.A little bit of statistics -- Appendix B. Proofs |
| ctrlnum | (ZDB-20-CBO)CR9781139207799 (OCoLC)825731371 (DE-599)BVBBV043945585 |
| dewey-full | 511.3/52 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 511 - General principles of mathematics |
| dewey-raw | 511.3/52 |
| dewey-search | 511.3/52 |
| dewey-sort | 3511.3 252 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik Philosophie |
| doi_str_mv | 10.1017/CBO9781139207799 |
| format | Electronic eBook |
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| id | DE-604.BV043945585 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-24T05:34:28Z |
| institution | BVB |
| isbn | 9781139207799 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029354556 |
| oclc_num | 825731371 |
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| owner_facet | DE-12 DE-92 DE-188 |
| physical | 1 Online-Ressource (vii, 259 Seiten) |
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| publishDate | 2013 |
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| publisher | Cambridge University Press |
| record_format | marc |
| spelling | Kleinberg, Samantha 1983- Verfasser (DE-588)1044034181 aut Causality, probability, and time Samantha Kleinberg, Stevens Institute of Technology, Hoboken, New Jersey Causality, Probability, & Time Cambridge Cambridge University Press 2013 1 Online-Ressource (vii, 259 Seiten) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) 1. Introduction -- 2. A brief history of causality -- 3. Probability, logic and probabilistic temporal logic -- 4. Defining causality -- 5. Inferring causality -- 6. Token causality -- 7. Case studies -- 8. Conclusion -- Appendix A.A little bit of statistics -- Appendix B. Proofs Causality is a key part of many fields and facets of life, from finding the relationship between diet and disease to discovering the reason for a particular stock market crash. Despite centuries of work in philosophy and decades of computational research, automated inference and explanation remains an open problem. In particular, the timing and complexity of relationships has been largely ignored even though this information is critically important for prediction, explanation and intervention. However, given the growing availability of large observational datasets including those from electronic health records and social networks, it is a practical necessity. This book presents a new approach to inference (finding relationships from a set of data) and explanation (assessing why a particular event occurred), addressing both the timing and complexity of relationships. The practical use of the method developed is illustrated through theoretical and experimental case studies, demonstrating its feasibility and success Computational complexity Kausalität (DE-588)4030102-3 gnd rswk-swf Komplexität (DE-588)4135369-9 gnd rswk-swf Berechnungskomplexität (DE-588)4134751-1 gnd rswk-swf Kausalität (DE-588)4030102-3 s Komplexität (DE-588)4135369-9 s 1\p DE-604 Berechnungskomplexität (DE-588)4134751-1 s 2\p DE-604 Erscheint auch als Druck-Ausgabe, Hardcover 978-1-107-02648-3 (DE-604)BV040442345 Erscheint auch als Druck-Ausgabe, Hardcover 978-1-107-68601-4 https://doi.org/10.1017/CBO9781139207799 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Kleinberg, Samantha 1983- Causality, probability, and time 1. Introduction -- 2. A brief history of causality -- 3. Probability, logic and probabilistic temporal logic -- 4. Defining causality -- 5. Inferring causality -- 6. Token causality -- 7. Case studies -- 8. Conclusion -- Appendix A.A little bit of statistics -- Appendix B. Proofs Computational complexity Kausalität (DE-588)4030102-3 gnd Komplexität (DE-588)4135369-9 gnd Berechnungskomplexität (DE-588)4134751-1 gnd |
| subject_GND | (DE-588)4030102-3 (DE-588)4135369-9 (DE-588)4134751-1 |
| title | Causality, probability, and time |
| title_alt | Causality, Probability, & Time |
| title_auth | Causality, probability, and time |
| title_exact_search | Causality, probability, and time |
| title_full | Causality, probability, and time Samantha Kleinberg, Stevens Institute of Technology, Hoboken, New Jersey |
| title_fullStr | Causality, probability, and time Samantha Kleinberg, Stevens Institute of Technology, Hoboken, New Jersey |
| title_full_unstemmed | Causality, probability, and time Samantha Kleinberg, Stevens Institute of Technology, Hoboken, New Jersey |
| title_short | Causality, probability, and time |
| title_sort | causality probability and time |
| topic | Computational complexity Kausalität (DE-588)4030102-3 gnd Komplexität (DE-588)4135369-9 gnd Berechnungskomplexität (DE-588)4134751-1 gnd |
| topic_facet | Computational complexity Kausalität Komplexität Berechnungskomplexität |
| url | https://doi.org/10.1017/CBO9781139207799 |
| work_keys_str_mv | AT kleinbergsamantha causalityprobabilityandtime AT kleinbergsamantha causalityprobabilitytime |