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102
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IJAR
2006
89views more  IJAR 2006»
15 years 15 days ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
105
Voted
CPC
2006
93views more  CPC 2006»
15 years 16 days ago
Generating Outerplanar Graphs Uniformly at Random
We show how to generate labeled and unlabeled outerplanar graphs with n vertices uniformly at random in polynomial time in n. To generate labeled outerplanar graphs, we present a c...
Manuel Bodirsky, Mihyun Kang
CORR
2010
Springer
160views Education» more  CORR 2010»
15 years 18 days ago
Scalable Probabilistic Databases with Factor Graphs and MCMC
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, forcing systems to sacrifice modeling power, scalability, or treatment of relatio...
Michael L. Wick, Andrew McCallum, Gerome Miklau
90
Voted
PCM
2004
Springer
107views Multimedia» more  PCM 2004»
15 years 5 months ago
Complete Performance Graphs in Probabilistic Information Retrieval
The performance of a Content-Based Image Retrieval (CBIR) system presented in the form of Precision-Recall or PrecisionScope graphs offers an incomplete overview of the system und...
Nicu Sebe, Dionysius P. Huijsmans, Qi Tian, Theo G...
119
Voted
TCSV
2008
202views more  TCSV 2008»
15 years 12 days ago
Probabilistic Object Tracking With Dynamic Attributed Relational Feature Graph
Object tracking is one of the fundamental problems in computer vision and has received considerable attention in the past two decades. The success of a tracking algorithm relies on...
Feng Tang, Hai Tao