1077 search results - page 48 / 216 » Learning network structure from passive measurements |
ISMDA
2001
Springer
14 years 5 days ago
2001
Springer
In recent years, a number of algorithms have been developed for learning the structure of Bayesian networks from data. In this paper we apply some of these algorithms to a realist...
MMNS
2003
13 years 9 months ago
2003
Abstract. The paper introduces a new receiver-based active end-toend measurement technique, called the Single-Double Unicast Probing (SDUP), to estimate the rate of losses which oc...
AUSAI
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
PPSN
2004
Springer
14 years 1 months ago
2004
Springer
Bayesian networks (BN) constitute a useful tool to model the joint distribution of a set of random variables of interest. To deal with the problem of learning sensible BN models fr...
CONEXT
2009
ACM
13 years 8 months ago
2009
ACM
An accurate Internet topology graph is important in many areas of networking, from deciding ISP business relationships to diagnosing network anomalies. Most Internet mapping effor...