1291 search results - page 75 / 259 » Learning Rules from Distributed Data |
116
click to vote
ICML
2008
IEEE
16 years 3 months ago
2008
IEEE
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
136
click to vote
ICDM
2003
IEEE
15 years 7 months ago
2003
IEEE
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
111
click to vote
FLAIRS
2006
15 years 3 months ago
2006
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
141
Voted
ACL
2012
13 years 5 months ago
2012
Most information extraction (IE) systems identify facts that are explicitly stated in text. However, in natural language, some facts are implicit, and identifying them requires ā...
117
Voted
IPPS
2000
IEEE
15 years 7 months ago
2000
IEEE
Discovering complex associations, anomalies and patterns in distributed data sets is gaining popularity in a range of scientiļ¬c, medical and business applications. Various algor...