613 search results - page 59 / 123 » Learning the Structure of Linear Latent Variable Models |
UAI
2003
13 years 10 months ago
2003
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
CIKM
2010
Springer
13 years 7 months ago
2010
Springer
: Collaborative Dual-PLSA: Mining Distinction and Commonality across Multiple Domains for Text Classification Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhon...
NN
2006
Springer
13 years 8 months ago
2006
Springer
The paper presents machine learning (ML) models that predict sedimentation in the harbour basin of the Port of Rotterdam. The important factors affecting the sedimentation process...
AUSAI
2005
Springer
14 years 2 months ago
2005
Springer
Abstract. Programmers employing inference in Bayesian networks typically rely on the inclusion of the model as well as an inference engine into their application. Sophisticated inf...
SDM
2004
SIAM
13 years 10 months ago
2004
SIAM
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...