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» The limitation of Bayesianism
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DCC
2010
IEEE
13 years 8 months ago
Neural Markovian Predictive Compression: An Algorithm for Online Lossless Data Compression
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
Erez Shermer, Mireille Avigal, Dana Shapira
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 10 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
ICDM
2009
IEEE
109views Data Mining» more  ICDM 2009»
14 years 4 months ago
Semi-naive Exploitation of One-Dependence Estimators
—It is well known that the key of Bayesian classifier learning is to balance the two important issues, that is, the exploration of attribute dependencies in high orders for ensu...
Nan Li, Yang Yu, Zhi-Hua Zhou
IJAR
2008
118views more  IJAR 2008»
13 years 10 months ago
Dynamic multiagent probabilistic inference
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...
Xiangdong An, Yang Xiang, Nick Cercone
FLAIRS
2006
13 years 11 months ago
Model Construction Algorithms for Object-Oriented Probabilistic Relational Models
This paper presents three new algorithms for the automatic construction of models from Object Oriented Probabilistic RelationalModels. The first two algorithms are based on the kn...
Catherine Howard, Markus Stumptner