Research map / Learning theory and algorithms / Sample complexity
Price of Parsimony: Complexity of Fourier Sparsity Testing
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Studies the computational complexity of testing whether a Boolean-domain real function over F_2^n is s-Fourier sparse, without prior knowledge of its sparsity.
Problem
Fourier sparsity testing: determining whether a function f: F_2^n -> R has at most s nonzero Fourier coefficients, when sparsity is not known in advance, since most learning algorithms assume it is known.
Approach
Analyzes the complexity of sparsity testing itself, quantifying the "price of parsimony" of not knowing the Fourier sparsity a priori; full text unavailable so specific technique is not stated in the abstract.
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