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» On Computing Functions with Uncertainty
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CIMAGING
2010
165views Hardware» more  CIMAGING 2010»
13 years 9 months ago
Implementation and evaluation of a penalized alternating minimization algorithm for computational DIC microscopy
We present the implementation and evaluation of a penalized alternating minimization (AM) method1 for the computation of a specimen's complex transmittance function (magnitud...
Chrysanthe Preza, Joseph A. O'Sullivan
AIPS
2006
13 years 10 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
CORR
2010
Springer
88views Education» more  CORR 2010»
13 years 9 months ago
A fuzzified BRAIN algorithm for learning DNF from incomplete data
Aim of this paper is to address the problem of learning Boolean functions from training data with missing values. We present an extension of the BRAIN algorithm, called U-BRAIN (U...
Salvatore Rampone, Ciro Russo
CORR
1998
Springer
142views Education» more  CORR 1998»
13 years 8 months ago
How to define a context-free backbone for DGs: Implementing a DG in the LFG formalism
This paper presents a multidimensional Dependency Grammar (DG), which decouples the dependency tree from word order, such that surface ordering is not determined by traversing the...
Norbert Bröker
IJCNN
2006
IEEE
14 years 3 months ago
Sparse Bayesian Models: Bankruptcy-Predictors of Choice?
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
Bernardete Ribeiro, Armando Vieira, João Ca...