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Combinatorics of Computing and Classification

This group gathers theorems where a combinatorial argument settles a question from computer science or from pattern recognition. It covers the sensitivity theorem, proved by Hao Huang in 2019, which states that the sensitivity of a Boolean function is at least the square root of its degree, and the ugly duckling theorem, an argument showing that classification is not really possible without some sort of bias because any two different objects share the same number of properties. Theorems about graphs and hypergraphs studied in their own right belong with Graph Theory or Ramsey Theory and Extremal Combinatorics.

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Combinatorics of Computing and Classification
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Ugly duckling theorem (Wikipedia)
Has Member: Ugly Duckling Theorem, Lead
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any two different objects share the same number of (extensional) properties
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Sensitivity theorem (Wikipedia)
Has Member: Sensitivity Theorem, Lead
Quote, Has Member: Sensitivity Theorem, Lead
the sensitivity theorem, proved by Hao Huang in 2019, states that the sensitivity of a Boolean function
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