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Electronic Colloquium on Computational Complexity

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Reports tagged with non-adaptive:
TR19-134 | 4th October 2019
Omri Ben-Eliezer, Clement Canonne, Shoham Letzter, Erik Waingarten

Finding monotone patterns in sublinear time

We study the problem of finding monotone subsequences in an array from the viewpoint of sublinear algorithms. For fixed $k \in \mathbb{N}$ and $\varepsilon > 0$, we show that the non-adaptive query complexity of finding a length-$k$ monotone subsequence of $f \colon [n] \to \mathbb{R}$, assuming that $f$ is $\varepsilon$-far ... more >>>

TR20-003 | 15th January 2020
Giuseppe Persiano, Kevin Yeo

Tight Static Lower Bounds for Non-Adaptive Data Structures

Revisions: 1

In this paper, we study the static cell probe complexity of non-adaptive data structures that maintain a subset of $n$ points from a universe consisting of $m=n^{1+\Omega(1)}$ points. A data structure is defined to be non-adaptive when the memory locations that are chosen to be accessed during a query depend ... more >>>

TR21-170 | 25th November 2021
Reyad Abed Elrazik, Robert Robere, Assaf Schuster, Gal Yehuda

Pseudorandom Self-Reductions for NP-Complete Problems

A language $L$ is random-self-reducible if deciding membership in $L$ can be reduced (in polynomial time) to deciding membership in $L$ for uniformly random instances. It is known that several "number theoretic" languages (such as computing the permanent of a matrix) admit random self-reductions. Feigenbaum and Fortnow showed that NP-complete ... more >>>

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