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» Randomized Variable Elimination
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FSS
2008
87views more  FSS 2008»
15 years 3 months ago
Representing parametric probabilistic models tainted with imprecision
Numerical possibility theory, belief function have been suggested as useful tools to represent imprecise, vague or incomplete information. They are particularly appropriate in unc...
Cédric Baudrit, Didier Dubois, Nathalie Per...
117
Voted
JILP
2000
103views more  JILP 2000»
15 years 3 months ago
Comparing and Combining Profiles
How much do two profiles of the same program differ? When has a profile changed enough to warrant reexamination of the profiled program? And how should two or more profiles be com...
Serap A. Savari, Cliff Young
QUESTA
2007
117views more  QUESTA 2007»
15 years 2 months ago
Estimating tail probabilities of heavy tailed distributions with asymptotically zero relative error
Efficient estimation of tail probabilities involving heavy tailed random variables is amongst the most challenging problems in Monte-Carlo simulation. In the last few years, appli...
Sandeep Juneja
147
Voted
SAC
2011
ACM
14 years 10 months ago
Slice sampling mixture models
We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
Maria Kalli, Jim E. Griffin, Stephen G. Walker
JCST
2010
189views more  JCST 2010»
14 years 10 months ago
Formally Analyzing Expected Time Complexity of Algorithms Using Theorem Proving
Probabilistic techniques are widely used in the analysis of algorithms to estimate the computational complexity of algorithms or a computational problem. Traditionally, such analys...
Osman Hasan, Sofiène Tahar