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Electronic Colloquium on Computational Complexity

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Reports tagged with Fourier analysis of Boolean functions:
TR06-065 | 24th May 2006
Jan Arpe, RĂ¼diger Reischuk

When Does Greedy Learning of Relevant Features Succeed? --- A Fourier-based Characterization ---

Detecting the relevant attributes of an unknown target concept
is an important and well studied problem in algorithmic learning.
Simple greedy strategies have been proposed that seem to perform reasonably
well in practice if a sufficiently large random subset of examples of the target
concept is provided.

Introducing a ... more >>>

TR11-146 | 1st November 2011
Bireswar Das, Manjish Pal, Vijay Visavaliya

The Entropy Influence Conjecture Revisited

In this paper, we prove that most of the boolean functions, $f : \{-1,1\}^n \rightarrow \{-1,1\}$
satisfy the Fourier Entropy Influence (FEI) Conjecture due to Friedgut and Kalai (Proc. AMS'96)\cite{FG96}. The conjecture says that the Entropy of a boolean function is at most a constant times the Influence of ... more >>>

TR14-088 | 13th July 2014
Swagato Sanyal

Sub-linear Upper Bounds on Fourier dimension of Boolean Functions in terms of Fourier sparsity

Revisions: 1 , Comments: 1

We prove that the Fourier dimension of any Boolean function with
Fourier sparsity $s$ is at most $O\left(s^{2/3}\right)$. Our proof
method yields an improved bound of $\widetilde{O}(\sqrt{s})$
assuming a conjecture of Tsang~\etal~\cite{tsang}, that for every
Boolean function of sparsity $s$ there is an affine subspace of
more >>>

TR17-147 | 3rd October 2017
Venkatesan Guruswami, Rishi Saket

Hardness of Rainbow Coloring Hypergraphs

A hypergraph is $k$-rainbow colorable if there exists a vertex coloring using $k$ colors such that each hyperedge has all the $k$ colors. Unlike usual hypergraph coloring, rainbow coloring becomes harder as the number of colors increases. This work studies the rainbow colorability of hypergraphs which are guaranteed to be ... more >>>

TR20-058 | 24th April 2020
Shafi Goldwasser, Guy Rothblum, Jonathan Shafer, Amir Yehudayoff

Interactive Proofs for Verifying Machine Learning

Revisions: 1

We consider the following question: using a source of labeled data and interaction with an untrusted prover, what is the complexity of verifying that a given hypothesis is "approximately correct"? We study interactive proof systems for PAC verification, where a verifier that interacts with a prover is required to accept ... more >>>

TR20-119 | 1st August 2020
Nikhil Mande, Swagato Sanyal

On parity decision trees for Fourier-sparse Boolean functions

We study parity decision trees for Boolean functions. The motivation of our study is the log-rank conjecture for XOR functions and its connection to Fourier analysis and parity decision tree complexity. Our contributions are as follows. Let $f : \mathbb{F}_2^n \to \{-1, 1\}$ be a Boolean function with Fourier support ... more >>>

TR20-121 | 3rd August 2020
Eshan Chattopadhyay, Jason Gaitonde, Abhishek Shetty

Fractional Pseudorandom Generators from the $k$th Fourier Level

Revisions: 2

In recent work by Chattopadhyay et al.[CHHL19,CHLT19], the authors exhibit a simple and flexible construction of pseudorandom generators for classes of Boolean functions that satisfy $L_1$ Fourier bounds. [CHHL19] show that if a class satisfies such tail bounds at all levels, this implies a PRG whose seed length depends on ... more >>>

TR20-128 | 3rd September 2020
Alexander A. Sherstov, Andrey Storozhenko, Pei Wu

An Optimal Separation of Randomized and Quantum Query Complexity

Revisions: 1

We prove that for every decision tree, the absolute values of the Fourier coefficients of given order $\ell\geq1$ sum to at most $c^{\ell}\sqrt{{d\choose\ell}(1+\log n)^{\ell-1}},$ where $n$ is the number of variables, $d$ is the tree depth, and $c>0$ is an absolute constant. This bound is essentially tight and settles a ... more >>>

TR20-163 | 5th November 2020
Gil Cohen, Noam Peri, Amnon Ta-Shma

Expander Random Walks: A Fourier-Analytic Approach

In this work we ask the following basic question: assume the vertices of an expander graph are labelled by $0,1$. What "test" functions $f : \{ 0,1\}^t \to \{0,1\}$ cannot distinguish $t$ independent samples from those obtained by a random walk? The expander hitting property due to Ajtai, Komlos and ... more >>>

TR21-046 | 22nd March 2021
Uma Girish, Avishay Tal, Kewen Wu

Fourier Growth of Parity Decision Trees

We prove that for every parity decision tree of depth $d$ on $n$ variables, the sum of absolute values of Fourier coefficients at level $\ell$ is at most $d^{\ell/2} \cdot O(\ell \cdot \log(n))^\ell$.
Our result is nearly tight for small values of $\ell$ and extends a previous Fourier bound ... more >>>

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