1077 search results - page 88 / 216 » Learning network structure from passive measurements |
JMLR
2006
13 years 7 months ago
2006
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
AMAI
2004
Springer
14 years 1 months ago
2004
Springer
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
IJCNN
2008
IEEE
14 years 2 months ago
2008
IEEE
— Machine learning has made great progress during the last decades and is being deployed in a wide range of applications. However, current machine learning techniques are far fro...
TELETRAFFIC
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. We focus in this paper on passive traffic measurement techniques that collect traces of TCP packets and analyze them to derive, for example, round-trip times or aggregate...
NIPS
1996
13 years 9 months ago
1996
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...