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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > KAAVE HOSSEINI:
All reports by Author Kaave Hosseini:

TR18-076 | 22nd April 2018
Abhishek Bhrushundi, Kaave Hosseini, Shachar Lovett, Sankeerth Rao

Torus polynomials: an algebraic approach to ACC lower bounds

Revisions: 1

We propose an algebraic approach to proving circuit lower bounds for ACC0 by defining and studying the notion of torus polynomials. We show how currently known polynomial-based approximation results for AC0 and ACC0 can be reformulated in this framework, implying that ACC0 can be approximated by low-degree torus polynomials. Furthermore, ... more >>>


TR18-015 | 25th January 2018
Eshan Chattopadhyay, Pooya Hatami, Kaave Hosseini, Shachar Lovett

Pseudorandom Generators from Polarizing Random Walks

Revisions: 1 , Comments: 1

We propose a new framework for constructing pseudorandom generators for $n$-variate Boolean functions. It is based on two new notions. First, we introduce fractional pseudorandom generators, which are pseudorandom distributions taking values in $[-1,1]^n$. Next, we use a fractional pseudorandom generator as steps of a random walk in $[-1,1]^n$ that ... more >>>


TR16-044 | 21st March 2016
Kaave Hosseini, Shachar Lovett

Structure of protocols for XOR functions

Revisions: 1

Let $f:\{0,1\}^n \to \{0,1\}$ be a boolean function. Its associated XOR function is the two-party function $f_\oplus(x,y) = f(x \oplus y)$.
We show that, up to polynomial factors, the deterministic communication complexity of $f_{\oplus}$ is equal to the parity decision tree complexity of $f$.
This relies on a novel technique ... more >>>


TR15-179 | 10th November 2015
Divesh Aggarwal, Kaave Hosseini, Shachar Lovett

Affine-malleable Extractors, Spectrum Doubling, and Application to Privacy Amplification

The study of seeded randomness extractors is a major line of research in theoretical computer science. The goal is to construct deterministic algorithms which can take a ``weak" random source $X$ with min-entropy $k$ and a uniformly random seed $Y$ of length $d$, and outputs a string of length close ... more >>>




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