ﻻ يوجد ملخص باللغة العربية
The majority problem is a special case of the heavy hitters problem. Given a collection of coloured balls, the task is to identify the majority colour or state that no such colour exists. Whilst the special case of two-colours has been well studied, the average-case performance for arbitrarily many colours has not. In this paper, we present heuristic analysis of the average-case performance of three deterministic algorithms that appear in the literature. We empirically validate our analysis with large scale simulations.
Many applications like pointer analysis and incremental compilation require maintaining a topological ordering of the nodes of a directed acyclic graph (DAG) under dynamic updates. All known algorithms for this problem are either only analyzed for wo
We consider an emph{approximate} version of the trace reconstruction problem, where the goal is to recover an unknown string $sin{0,1}^n$ from $m$ traces (each trace is generated independently by passing $s$ through a probabilistic insertion-deletion
We consider the sensitivity of algorithms for the maximum matching problem against edge and vertex modifications. Algorithms with low sensitivity are desirable because they are robust to edge failure or attack. In this work, we show a randomized $(1-
We study the problems of testing isomorphism of polynomials, algebras, and multilinear forms. Our first main results are average-case algorithms for these problems. For example, we develop an algorithm that takes two cubic forms $f, gin mathbb{F}_q[x
Digital Elevation Models (DEMs) are important datasets for modelling the line of sight, such as radio signals, sound waves and human vision. These are commonly analyzed using rotational sweep algorithms. However, such algorithms require large numbers