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UAI
1997
15 years 5 months ago
A Bayesian Approach to Learning Bayesian Networks with Local Structure
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
JACM
2000
131views more  JACM 2000»
15 years 3 months ago
The soft heap: an approximate priority queue with optimal error rate
A simple variant of a priority queue, called a soft heap, is introduced. The data structure supports the usual operations: insert, delete, meld, and findmin. Its novelty is to beat...
Bernard Chazelle
145
Voted
UAI
1996
15 years 5 months ago
Learning Bayesian Networks with Local Structure
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Nir Friedman, Moisés Goldszmidt
WWW
2008
ACM
16 years 4 months ago
Statistical properties of community structure in large social and information networks
A large body of work has been devoted to identifying community structure in networks. A community is often though of as a set of nodes that has more connections between its member...
Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Mi...
154
Voted
TSP
2011
197views more  TSP 2011»
14 years 11 months ago
Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods
—This paper proposes a technique for motion estimation of groups of targets based on evolving graph networks. The main novelty over alternative group tracking techniques stems fr...
Amadou Gning, Lyudmila Mihaylova, Simon Maskell, S...