15 search results - page 1 / 3 » Maximum Margin Learning with Incomplete Data: Learning Netwo... |
JMLR
2010
12 years 11 months ago
2010
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
UAI
1996
13 years 5 months ago
1996
We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomp...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
ICML
2008
IEEE
14 years 5 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...
HIS
2003
13 years 5 months ago
2003
– Probabilistic Inference Networks are becoming increasingly popular for modeling and reasoning in uncertain domains. In the past few years, many efforts have been made in learni...