553 search results - page 34 / 111 » Bayesian network learning algorithms using structural restri... |
JMLR
2010
14 years 4 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
96
Voted
KDD
2010
ACM
15 years 1 months ago
2010
ACM
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
ICANNGA
2009
Springer
15 years 4 months ago
2009
Springer
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...
92
Voted
UAI
2004
14 years 11 months ago
2004
Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the perfo...
ICA
2010
Springer
14 years 10 months ago
2010
Springer
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...