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» Hybrid Soft Computing: Where are we Going
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UAI
2001
13 years 9 months ago
Exact Inference in Networks with Discrete Children of Continuous Parents
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
Uri Lerner, Eran Segal, Daphne Koller
TNN
2010
174views Management» more  TNN 2010»
13 years 2 months ago
Equivalences between neural-autoregressive time series models and fuzzy systems
Soft computing (SC) emerged as an integrating framework for a number of techniques that could complement one another quite well (artificial neural networks, fuzzy systems, evolutio...
José Luis Aznarte, José Manuel Ben&i...
ICPR
2008
IEEE
14 years 2 months ago
Robust recognition of 1-D barcodes using camera phones
In this paper we present an algorithm for the recognition of 1D barcodes using camera phones, which is highly robust regarding the the typical image distortions. We have created a...
Steffen Wachenfeld, Sebastian Terlunen, Xiaoyi Jia...
SIGMOD
1999
ACM
98views Database» more  SIGMOD 1999»
13 years 12 months ago
Integration of Spatial Join Algorithms for Processing Multiple Inputs
Several techniques that compute the join between two spatial datasets have been proposed during the last decade. Among these methods, some consider existing indices for the joined...
Nikos Mamoulis, Dimitris Papadias
SDM
2008
SIAM
134views Data Mining» more  SDM 2008»
13 years 9 months ago
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...