99 search results - page 9 / 20 » Learning Causal Structure from Overlapping Variable Sets |
KDD
2007
ACM
16 years 2 days ago
2007
ACM
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
97
Voted
ICML
2009
IEEE
16 years 14 days ago
2009
IEEE
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
86
Voted
VMCAI
2005
Springer
15 years 5 months ago
2005
Springer
Abstract. It is a hotly researching topic to eliminate irrelevant variables from counterexample, to make it easier to be understood. K Ravi proposes a two-stages counterexample min...
108
Voted
DMIN
2006
15 years 1 months ago
2006
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
149
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CVPR
2012
IEEE
13 years 2 months ago
2012
IEEE
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...