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» AS Relationships: Inference and Validation
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NIPS
2000
14 years 11 months ago
Structure Learning in Human Causal Induction
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
Joshua B. Tenenbaum, Thomas L. Griffiths
UAI
1998
14 years 11 months ago
Incremental Tradeoff Resolution in Qualitative Probabilistic Networks
Qualitativeprobabilistic reasoningin a Bayesiannetworkoften reveals tradeoffs: relationships that are ambiguousdue to competingqualitative influences. Wepresent twotechniquesthat ...
Chao-Lin Liu, Michael P. Wellman
FAST
2009
14 years 7 months ago
Steps Toward Managing Lineage Metadata in Grid Clusters
The lineage of a piece of data is of utility to a wide range of domains. Several application-specific extensions have been built to facilitate tracking the origin of the output th...
Ashish Gehani, Minyoung Kim, Jian Zhang
ICDAR
2005
IEEE
15 years 3 months ago
Historical Recall and Precision: Summarizing Generated Hypotheses
Document recognition involves many kinds of hypotheses: segmentation hypotheses, classification hypotheses, spatial relationship hypotheses, and so on. Many recognition strategie...
Richard Zanibbi, Dorothea Blostein, James R. Cordy
CIE
2007
Springer
15 years 4 months ago
Input-Dependence in Function-Learning
In the standard model of inductive inference, a learner gets as input the graph of a function, and has to discover (in the limit) a program for the function. In this paper, we cons...
Sanjay Jain, Eric Martin, Frank Stephan