Title
Optimal query complexity bounds for finding graphs
Abstract
We consider the problem of finding an unknown graph by using two types of queries with an additive property. Given a graph, an additive query asks the number of edges in a set of vertices while a cross-additive query asks the number of edges crossing between two disjoint sets of vertices. The queries ask sum of weights for the weighted graphs. These types of queries were partially motivated in DNA shotgun sequencing and linkage discovery problem of artificial intelligence. For a given unknown weighted graph G with n vertices, m edges, and a certain mild condition on weights, we prove that there exists a non-adaptive algorithm to find the edges of G using O(m log n / log m) queries of both types provided that m ≥ nε for any constant ε 0. For an unweighted graph, it is shown that the same bound holds for all range of m. This settles a conjecture of Grebinski [23] for finding an unweighted graph using additive queries. We also consider the problem of finding the Fourier coefficients of a certain class of pseudo-Boolean functions. A similar coin weighing problem is also considered.
Year
DOI
Venue
2008
10.1145/1374376.1374484
Artif. Intell.
Keywords
Field
DocType
artificial intelligent,combinatorial search,fourier coefficient,group testing
Discrete mathematics,Strength of a graph,Combinatorics,Path (graph theory),Hypercube graph,Graph labeling,Cycle graph,Mixed graph,Mathematics,Complement graph,Path graph
Conference
Volume
Issue
ISSN
174
9-10
0737-8017
Citations 
PageRank 
References 
15
0.81
21
Authors
2
Name
Order
Citations
PageRank
Sung-Soon Choi111211.03
Jeong Han Kim269960.19