This chapter is devoted to linear threshold functions, their generalization to higher degrees, and their exemplar the majority function. The study of LTFs leads naturally to the introduction of the Central Limit Theorem and Gaussian random variables — important tools in analysis of boolean functions. We will first use these tools to analyze [...]
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[...] [...] Having derived strong results about the Fourier spectrum of small DNFs and CNFs, we will now extend to the case of constant-depth circuits. We begin by describing how Håstad applied his Switching Lemma to constant-depth circuits. We then describe some Fourier-theoretic consequences coming from a very early (1989) work in analysis of boolean functions [...] Let’s further investigate how random restrictions can simplify DNF formulas. [...] In this section we describe the method of applying random restrictions. This is a very “Fourier-friendly” way of simplifying a boolean function. [...] In this section we study the tribes DNF formulas, which serve as an important examples and counterexamples in analysis of boolean functions. Perhaps the most notable feature of the tribes function is that (for a suitable choice of parameters) it is essentially unbiased and yet all of its influences are quite tiny. [...] Perhaps the commonest way of representing a boolean function $f : \{0,1\}^n \to \{0,1\}$ is by a DNF formula: [...] In this chapter we investigate boolean functions representable by small DNF formulas and constant-depth circuits; these are significant generalizations of decision trees. Besides being natural from a computational point of view, these representation classes are close to the limit of what complexity theorists can “understand” (e.g., prove explicit lower bounds for). One reason [...] The fact that the Fourier characters $\chi_{\gamma} : {\mathbb F}_2^n \to \{-1,1\}$ form a group isomorphic to ${\mathbb F}_2^n$ is not a coincidence; the analogous result holds for any finite abelian group and is a special case of the theory of Pontryagin duality in harmonic analysis. We will see further examples of this in Chapter [...] |
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