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AI
2006
Springer
13 years 5 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
CORR
2011
Springer
169views Education» more  CORR 2011»
12 years 9 months ago
Pseudo-random graphs and bit probe schemes with one-sided error
We study probabilistic bit-probe schemes for the membership problem. Given a set A of at most n elements from the universe of size m we organize such a structure that queries of t...
Andrei E. Romashchenko
JGAA
2007
142views more  JGAA 2007»
13 years 5 months ago
Approximation Algorithms for the Maximum Induced Planar and Outerplanar Subgraph Problems
The task of finding the largest subset of vertices of a graph that induces a planar subgraph is known as the Maximum Induced Planar Subgraph problem (MIPS). In this paper, some n...
Kerri Morgan, Graham Farr
COMBINATORICS
2000
114views more  COMBINATORICS 2000»
13 years 5 months ago
Trees and Matchings
In this article, Temperley's bijection between spanning trees of the square grid on the one hand, and perfect matchings (also known as dimer coverings) of the square grid on ...
Richard Kenyon, James Gary Propp, David Bruce Wils...
CP
2000
Springer
13 years 9 months ago
Automatic Generation of Propagation Rules for Finite Domains
plexity Theorems: Talk Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 David McAllester Regular Papers Automatic Generation of Propagation Rules for F...
Slim Abdennadher, Christophe Rigotti