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IJAR
2006
89views more  IJAR 2006»
15 years 3 months 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
IJCAI
2003
15 years 4 months ago
Optimal Time-Space Tradeoff in Probabilistic Inference
Recursive Conditioning, RC, is an any-space algorithm lor exact inference in Bayesian networks, which can trade space for time in increments of the size of a floating point number...
David Allen, Adnan Darwiche
122
Voted
STOC
2005
ACM
113views Algorithms» more  STOC 2005»
16 years 3 months ago
Efficient testing of groups
We construct an efficient probabilistic algorithm that, given a finite set with a binary operation, tests if it is an abelian group. The distance used is an analogue of the edit d...
Katalin Friedl, Gábor Ivanyos, Miklos Santh...
ILP
2007
Springer
15 years 9 months ago
Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates
Statistical Relational Learning (SRL) combines the benefits of probabilistic machine learning approaches with complex, structured domains from Inductive Logic Programming (ILP). W...
Mark Goadrich, Jude W. Shavlik
132
Voted
TACAS
2000
Springer
138views Algorithms» more  TACAS 2000»
15 years 7 months ago
Symbolic Model Checking of Probabilistic Processes Using MTBDDs and the Kronecker Representation
This paper reports on experimental results with symbolic model checking of probabilistic processes based on Multi-Terminal Binary Decision Diagrams (MTBDDs). We consider concurrent...
Luca de Alfaro, Marta Z. Kwiatkowska, Gethin Norma...