Improved Approximation of Linear Threshold Functions

Ilias Diakonikolas, Rocco A. Servedio

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We prove two main results on how arbitrary linear threshold functions $f(x) = \sign(w\cdot x - \theta)$ over the $n$-dimensional Boolean hypercube can be approximated by simple threshold functions. Our first result shows that every $n$-variable threshold function $f$ is $\eps$-close to a threshold function depending only on $\Inf(f)^2 \cdot \poly(1/\eps)$ many variables, where $\Inf(f)$ denotes the total influence or average sensitivity of $f.$ This is an exponential sharpening of Friedgut's well-known theorem \cite{Friedgut:98}, which states that every Boolean function $f$ is $\eps$-close to a function depending only on $2^{O(\Inf(f)/\eps)}$ many variables, for the case of threshold functions. We complement this upper bound by showing that $\Omega(\Inf(f)^2 + 1/\epsilon^2)$ many variables are required for $\epsilon$-approximating threshold functions. Our second result is a proof that every $n$-variable threshold function is $\eps$-close to a threshold function with integer weights at most $\poly(n) \cdot 2^{\tilde{O}(1/\eps^{2/3})}.$ This is a significant improvement, in the dependence on the error parameter $\eps$, on an earlier result of \cite{Servedio:07cc} which gave a $\poly(n) \cdot 2^{\tilde{O}(1/\eps^{2})}$ bound. Our improvement is obtained via a new proof technique that uses strong anti-concentration bounds from probability theory. The new technique also gives a simple and modular proof of the original \cite{Servedio:07cc} result, and extends to give low-weight approximators for threshold functions under a range of probability distributions beyond just the uniform distribution.
Original languageEnglish
Title of host publicationComputational Complexity, 2009. CCC '09. 24th Annual IEEE Conference on
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages12
ISBN (Print)978-0-7695-3717-7
Publication statusPublished - 2009


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