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» Ontology-Based Generation of Bayesian Networks
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JMLR
2010
157views more  JMLR 2010»
13 years 5 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
ICCV
2005
IEEE
15 years 23 days ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
KDD
1999
ACM
128views Data Mining» more  KDD 1999»
14 years 3 months ago
Towards Automated Synthesis of Data Mining Programs
Code synthesis is routinely used in industry to generate GUIs, form lling applications, and database support code and is even used with COBOL. In this paper we consider the questi...
Wray L. Buntine, Bernd Fischer 0002, Thomas Pressb...
AI
2002
Springer
13 years 10 months ago
The size distribution for Markov equivalence classes of acyclic digraph models
Bayesian networks, equivalently graphical Markov models determined by acyclic digraphs or ADGs (also called directed acyclic graphs or dags), have proved to be both effective and ...
Steven B. Gillispie, Michael D. Perlman
WWW
2008
ACM
14 years 11 months ago
Exploring social annotations for information retrieval
Social annotation has gained increasing popularity in many Web-based applications, leading to an emerging research area in text analysis and information retrieval. This paper is c...
Ding Zhou, Jiang Bian, Shuyi Zheng, Hongyuan Zha, ...