Simpler Analyses of Union-Find

08/17/2023
by   Zhiyi Huang, et al.
0

We analyze union-find using potential functions motivated by continuous algorithms, and give alternate proofs of the O(loglogn), O(log^*n), O(log^**n), and O(α(n)) amortized cost upper bounds. The proof of the O(loglogn) amortized bound goes as follows. Let each node's potential be the square root of its size, i.e., the size of the subtree rooted from it. The overall potential increase is O(n) because the node sizes increase geometrically along any tree path. When compressing a path, each node on the path satisfies that either its potential decreases by Ω(1), or its child's size along the path is less than the square root of its size: this can happen at most O(loglogn) times along any tree path.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/15/2017

Optimal top dag compression

It is shown that for a given ordered node-labelled tree of size n and wi...
research
11/18/2019

Top-down induction of decision trees: rigorous guarantees and inherent limitations

Consider the following heuristic for building a decision tree for a func...
research
05/16/2022

Optimal chromatic bound for (P_2+P_3, P̅_̅2̅+̅ ̅P̅_̅3̅)-free graphs

For a graph G, let χ(G) (ω(G)) denote its chromatic (clique) number. A P...
research
04/01/2019

Boundedness of Conjunctive Regular Path Queries

We study the boundedness problem for unions of conjunctive regular path ...
research
12/27/2021

How to choose the root: centrality measures over tree structures

Centrality measures are commonly used to analyze graph-structured data; ...
research
03/28/2017

RootJS: Node.js Bindings for ROOT 6

We present rootJS, an interface making it possible to seamlessly integra...
research
05/06/2015

Retaining Experience and Growing Solutions

Generally, when genetic programming (GP) is used for function synthesis ...

Please sign up or login with your details

Forgot password? Click here to reset