220 search results - page 6 / 44 » Learning probabilistic decision graphs |
PKDD
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. Gaussian processes have successfully been used to learn preferences among entities as they provide nonparametric Bayesian approaches for model selection and probabilistic...
ICALP
2001
Springer
13 years 12 months ago
2001
Springer
We prove a lower bound of (n4/3 log1/3 n) on the randomized decision tree complexity of any nontrivial monotone n-vertex graph property, and of any nontrivial monotone bipartite g...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
MLG
2007
Springer
14 years 1 months ago
2007
Springer
Recent investigations [12, 2, 8, 5, 6] and [11, 9] indicate the use of a probabilistic (’learning’) perspective of tasks defined on a single graph, as opposed to the traditio...
DAC
1994
ACM
13 years 11 months ago
1994
ACM
Regarding nite state machines as Markov chains facilitates the application of probabilistic methods to very large logic synthesis and formal veri cation problems. Recently, we ha...