All reports by Author Jesse Goodman:

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TR20-106
| 15th July 2020
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Eshan Chattopadhyay, Jesse Goodman#### Explicit Extremal Designs and Applications to Extractors

Revisions: 4

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TR20-060
| 23rd April 2020
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Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Xin Li#### Leakage-Resilient Extractors and Secret-Sharing against Bounded Collusion Protocols

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TR19-184
| 13th December 2019
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Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Xin Li#### Extractors for Adversarial Sources via Extremal Hypergraphs

Eshan Chattopadhyay, Jesse Goodman

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 >>>

Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Xin Li

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 >>>

Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Xin Li

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 >>>