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CORR
2010
Springer
88views Education» more  CORR 2010»
13 years 8 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
ICASSP
2008
IEEE
14 years 3 months ago
Statistical approach to vocal tract transfer function estimation based on factor analyzed trajectory HMM
In this paper, we describe a novel statistical approach to the vocal tract transfer function (VTTF) estimation of a speech signal based on a factor analyzed trajectory hidden Mark...
Tomoki Toda, Keiichi Tokuda
HIS
2003
13 years 10 months ago
A Hybrid Approach for Learning Parameters of Probabilistic Networks from Incomplete Databases
– Probabilistic Inference Networks are becoming increasingly popular for modeling and reasoning in uncertain domains. In the past few years, many efforts have been made in learni...
S. Haider
JPDC
2006
83views more  JPDC 2006»
13 years 8 months ago
Virtual Leashing: Creating a computational foundation for software protection
We introduce Virtual Leashing,1 a new technique for software protection and control. The leashing process removes small fragments of code, pervasive throughout the application, an...
Ori Dvir, Maurice Herlihy, Nir Shavit
CSDA
2007
100views more  CSDA 2007»
13 years 8 months ago
Convergence of random k-nearest-neighbour imputation
Random k-nearest-neighbour (RKNN) imputation is an established algorithm for filling in missing values in data sets. Assume that data are missing in a random way, so that missing...
Fredrik A. Dahl