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ML
2006
ACM
122views Machine Learning» more  ML 2006»
13 years 9 months ago
PRL: A probabilistic relational language
In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
Lise Getoor, John Grant
CIKM
2010
Springer
13 years 7 months ago
Utilizing re-finding for personalized information retrieval
Individuals often use search engines to return to web pages they have previously visited. This behaviour, called refinding, accounts for about 38% of all queries. While researcher...
Sarah K. Tyler, Jian Wang, Yi Zhang 0001
CONTEXT
2001
Springer
14 years 1 months ago
Belief Expansion, Contextual Fit, and the Reliability of Information Sources
We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability...
Luc Bovens, Stephan Hartmann
NIPS
2008
13 years 10 months ago
The Mondrian Process
We describe a novel class of distributions, called Mondrian processes, which can be interpreted as probability distributions over kd-tree data structures. Mondrian processes are m...
Daniel M. Roy, Yee Whye Teh
AAAI
2004
13 years 10 months ago
Identifying Linear Causal Effects
This paper concerns the assessment of linear cause-effect relationships from a combination of observational data and qualitative causal structures. The paper shows how techniques ...
Jin Tian