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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > JESSE GOODMAN:
All reports by Author Jesse Goodman:

TR21-106 | 22nd July 2021
Eshan Chattopadhyay, Jesse Goodman, David Zuckerman

The Space Complexity of Sampling

Recently, there has been exciting progress in understanding the complexity of distributions. Here, the goal is to quantify the resources required to generate (or sample) a distribution. Proving lower bounds in this new setting is more challenging than in the classical setting, and has yielded interesting new techniques and surprising ... more >>>


TR21-075 | 4th June 2021
Eshan Chattopadhyay, Jesse Goodman, Jyun-Jie Liao

Affine Extractors for Almost Logarithmic Entropy

We give an explicit construction of an affine extractor (over $\mathbb{F}_2$) that works for affine sources on $n$ bits with min-entropy $k \ge~ \log n \cdot (\log \log n)^{1 + o(1)}$. This improves prior work of Li (FOCS'16) that requires min-entropy at least $\mathrm{poly}(\log n)$.

Our construction is ... more >>>


TR20-106 | 15th July 2020
Eshan Chattopadhyay, Jesse Goodman

Explicit Extremal Designs and Applications to Extractors

Revisions: 5

An $(n,r,s)$-design, or $(n,r,s)$-partial Steiner system, is an $r$-uniform hypergraph over $n$ vertices with pairwise hyperedge intersections of size $0$, we extract from $(N,K,n,k)$-adversarial sources of locality $0$, where $K\geq N^\delta$ and $k\geq\text{polylog }n$. The previous best result (Chattopadhyay et al., STOC 2020) required $K\geq N^{1/2+o(1)}$. As a result, we ... more >>>


TR20-060 | 23rd April 2020
Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Xin Li

Leakage-Resilient Extractors and Secret-Sharing against Bounded Collusion Protocols

In a recent work, Kumar, Meka, and Sahai (FOCS 2019) introduced the notion of bounded collusion protocols (BCPs), in which $N$ parties wish to compute some joint function $f:(\{0,1\}^n)^N\to\{0,1\}$ using a public blackboard, but such that only $p$ parties may collude at a time. This generalizes well studied models in ... more >>>


TR19-184 | 13th December 2019
Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Xin Li

Extractors for Adversarial Sources via Extremal Hypergraphs

Randomness extraction is a fundamental problem that has been studied for over three decades. A well-studied setting assumes that one has access to multiple independent weak random sources, each with some entropy. However, this assumption is often unrealistic in practice. In real life, natural sources of randomness can produce samples ... more >>>




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