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» Learning associative Markov networks
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ECAI
2004
Springer
14 years 1 months ago
Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
Evelina Lamma, Fabrizio Riguzzi, Sergio Storari
CORR
2010
Springer
175views Education» more  CORR 2010»
13 years 2 months ago
On the Combinatorial Multi-Armed Bandit Problem with Markovian Rewards
We consider a combinatorial generalization of the classical multi-armed bandit problem that is defined as follows. There is a given bipartite graph of M users and N M resources. F...
Yi Gai, Bhaskar Krishnamachari, Mingyan Liu
AI
2006
Springer
13 years 8 months ago
Robot introspection through learned hidden Markov models
In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behaviour...
Maria Fox, Malik Ghallab, Guillaume Infantes, Dere...
ISNN
2007
Springer
14 years 2 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li
CCECE
2006
IEEE
14 years 1 months ago
A Dynamic Associative E-Learning Model based on a Spreading Activation Network
Presenting information to an e-learning environment is a challenge, mostly, because ofthe hypertextlhypermedia nature and the richness ofthe context and information provides. This...
Phongchai Nilas, Nilamit Nilas, Somsak Mitatha