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Electronic Colloquium on Computational Complexity

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REPORTS > KEYWORD > LITTLEWOOD-OFFORD:
Reports tagged with Littlewood-Offord:
TR15-188 | 24th November 2015
Daniel Kane, Ryan Williams

Super-Linear Gate and Super-Quadratic Wire Lower Bounds for Depth-Two and Depth-Three Threshold Circuits

In order to formally understand the power of neural computing, we first need to crack the frontier of threshold circuits with two and three layers, a regime that has been surprisingly intractable to analyze. We prove the first super-linear gate lower bounds and the first super-quadratic wire lower bounds for ... more >>>


TR17-026 | 17th February 2017
Valentine Kabanets, Daniel Kane, Zhenjian Lu

A Polynomial Restriction Lemma with Applications

A polynomial threshold function (PTF) of degree $d$ is a boolean function of the form $f=\mathrm{sgn}(p)$, where $p$ is a degree-$d$ polynomial, and $\mathrm{sgn}$ is the sign function. The main result of the paper is an almost optimal bound on the probability that a random restriction of a PTF is ... more >>>


TR18-145 | 13th August 2018
Ryan O'Donnell, Rocco Servedio, Li-Yang Tan

Fooling Polytopes

We give a pseudorandom generator that fools $m$-facet polytopes over $\{0,1\}^n$ with seed length $\mathrm{polylog}(m) \cdot \log n$. The previous best seed length had superlinear dependence on $m$. An immediate consequence is a deterministic quasipolynomial time algorithm for approximating the number of solutions to any $\{0,1\}$-integer program.

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TR24-151 | 2nd October 2024
Vijay Bhattiprolu, Euiwoong Lee

Inapproximability of Sparsest Vector in a Real Subspace

Revisions: 1

We establish strong inapproximability for finding the sparsest nonzero vector in a real subspace (where sparsity refers to the number of nonzero entries). Formally we show that it is NP-Hard (under randomized reductions) to approximate the sparsest vector in a subspace within any constant factor. By simple tensoring the inapproximability ... more >>>




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