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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > DAVID ZUCKERMAN:
All reports by Author David Zuckerman:

TR24-165 | 21st October 2024
Dean Doron, Dana Moshkovitz, Justin Oh, David Zuckerman

Online Condensing of Unpredictable Sources via Random Walks

A natural model of a source of randomness consists of a long stream of symbols $X = X_1\circ\ldots\circ X_t$, with some guarantee on the entropy of $X_i$ conditioned on the outcome of the prefix $x_1,\dots,x_{i-1}$. We study unpredictable sources, a generalization of the almost Chor--Goldreich (CG) sources considered in [DMOZ23]. ... more >>>


TR24-097 | 31st May 2024
Zhiyang Xun, David Zuckerman

Near-Optimal Averaging Samplers

Revisions: 4

We present the first efficient averaging sampler that achieves asymptotically optimal randomness complexity and near-optimal sample complexity for natural parameter choices. Specifically, for any constant $\alpha > 0$, for $\delta > 2^{-\mathrm{poly}(1 / \varepsilon)}$, it uses $m + O(\log (1 / \delta))$ random bits to output $t = O(\log(1 ... more >>>


TR22-169 | 26th November 2022
Zeyu Guo, Ben Lee Volk, Akhil Jalan, David Zuckerman

Extractors for Images of Varieties

Revisions: 1

We construct explicit deterministic extractors for polynomial images of varieties, that is, distributions sampled by applying a low-degree polynomial map $f : \mathbb{F}_q^r \to \mathbb{F}_q^n$ to an element sampled uniformly at random from a $k$-dimensional variety $V \subseteq \mathbb{F}_q^r$. This class of sources generalizes both polynomial sources, studied by Dvir, ... more >>>




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