FOCM
2006
13 years 4 months ago
2006
Let be an unknown Borel measure defined on the space Z := X
CORR
2006
Springer
13 years 4 months ago
2006
Springer
In multi-criteria optimization, several objective functions are to be optimized. Since the different objective functions are usually in conflict with each other, one cannot conside...
COMPUTING
2006
13 years 4 months ago
2006
Radial functions are a powerful tool in many areas of multidimensional approximation, especially when dealing with scattered data. We present a fast approximate algorithm for the ...
ADCM
2008
13 years 4 months ago
2008
In this paper we analyse a hybrid approximation of functions on the sphere S2 R3 by radial basis functions combined with polynomials, with the radial basis functions assumed to be...
UAI
1996
13 years 5 months ago
1996
We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomp...
UAI
2000
13 years 5 months ago
2000
We consider the problem belief-state monitoring for the purposes of implementing a policy for a partially-observable Markov decision process (POMDP), specifically how one might ap...
NC
1998
13 years 5 months ago
1998
In this paper a new approach for approximation problems involving only few input and output parameters is presented and compared to traditional Backpropagation Neural Networks (BP...
AAAI
1997
13 years 5 months ago
1997
The problem of counting the number of solutions to a constraint satisfaction problem (CSP) is rephrased in terms of probability updating in Bayes networks. Approximating the proba...
NIPS
2003
13 years 5 months ago
2003
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
FLAIRS
2003
13 years 5 months ago
2003
This paper deals with the problem of merging descriptions of approximate spatial location specified at different levels of granularity. We distinguish between the roughness of an...