Algorithmic Information Theory is a branch of information theory that quantifies the complexity of data by defining the information content of an object as the length of the shortest possible computer program that can reproduce it, distinguishing it from other information measures by grounding information in computational describability rather than probabilistic entropy.
543
Publications
52.5K
Citations
1.2K
Authors
559
Institutions
Publications per year
2017–2026
126
Variants
Ait
Parents
Publications
543
Information theory, inference, and learning algorithms
Choice Reviews Online · 2004 · 6.6K citations
Information Theory, Inference, and Learning Algorithms
Kybernetes · 2004 · 5.1K citations
Toward optimal feature selection
Daphne Koller, Mehran Sahami · 1996 · 1.4K citations
1–5 of 543
Authors
1.2K
- HZ
10
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- GJ
9
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- PV
8
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- AA
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- PG
5
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1–5 of 1.2K
Institutions
559
University of Oxford
Oxford, United Kingdom
10 h-index
24 publications
1.3K citations
Stanford University
Stanford, United States
10 h-index
20 publications
1.7K citations
Karolinska Institutet
Stockholm, Sweden
8 h-index
26 publications
662 citations
Centrum Wiskunde & Informatica
Amsterdam, The Netherlands
8 h-index
9 publications
544 citations
IBM (United States)
Armonk, United States
7 h-index
7 publications
391 citations
University of Florida
Gainesville, United States
7 h-index
14 publications
380 citations
University of Amsterdam
Amsterdam, The Netherlands
7 h-index
7 publications
299 citations
Santa Fe Institute
Santa Fe, United States
6 h-index
10 publications
952 citations
1–8 of 559
Venues
- IEEE Transactions on Information Theory
24 publications · 2.5K citations
19
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- arXiv (Cornell University)
Repository · 34 publications · 1K citations
18
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- Entropy
15 publications · 446 citations
12
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- Proceedings of the National Academy of Sciences
PNAS · 6 publications · 639 citations
6
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- ArXiv.org
Repository · 5 publications · 136 citations
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