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Ancestor Relations in the Presence of Unobserved Variables
Published on Oct 03, 20112674 Views
Bayesian networks (BNs) are an appealing model for causal and noncausal dependencies among a set of variables. Learning BNs from observational data is challenging due to the nonidentifiability of th
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Chapter list
Ancestor Relations in the Presence of Unobserved Variables00:00
Outline00:09
Bayesian networks (1)00:35
Bayesian networks (2)01:29
Structure Discovery02:14
Approaches03:29
Structural features04:33
Ancestor relations (1)06:06
Ancestor relations (2)07:00
Algorithm08:45
Assumptions09:07
Dynamic programming - outline (1)09:49
Dynamic programming - outline (2)11:05
Dynamic programming - outline (3)11:49
Time and space complexity12:58
Learning power13:41
Full vs. partial Bayesian averaging14:40
Conclusions16:30
Thank you!17:02