In many settings, Booleanfunctions provide a natural way to describe such influences.
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Each measure provides a unique window into the structure of the Booleanfunction.
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Over the years, computer scientists have developed many ways to measure the complexity of a given Booleanfunction.
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Results: We put forward a statistical model for sparse, noisy Booleanfunctions and methods for inference under the model.
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This motivates a need for statistical methods capable of making inferences regarding Booleanfunctions under conditions of noise and sparsity.
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This process is a Booleanfunction: Your answers are the input bits, and the banker's decision is the output bit.
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A Booleanfunction evaluates to one of three values: TRUE (1), FALSE (0), or NULL.
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For instance, the "sensitivity" of a Booleanfunction tracks, roughly speaking, the likelihood that flipping a single input bit will alter the output bit.
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The conjecture concerns Booleanfunctions, rules for transforming a string of input bits (0s and 1s) into a single output bit.