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» Using Markov Blankets for Causal Structure Learning
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ICMLA
2007
15 years 5 months ago
Learning bayesian networks consistent with the optimal branching
We introduce a polynomial-time algorithm to learn Bayesian networks whose structure is restricted to nodes with in-degree at most k and to edges consistent with the optimal branch...
Alexandra M. Carvalho, Arlindo L. Oliveira
124
Voted
JETAI
1998
110views more  JETAI 1998»
15 years 3 months ago
Independency relationships and learning algorithms for singly connected networks
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
Luis M. de Campos
145
Voted
ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
15 years 9 months ago
Mining Complex Time-Series Data by Learning Markovian Models
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
144
Voted
ATAL
2006
Springer
15 years 7 months ago
Learning executable agent behaviors from observation
We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we ...
Andrew Guillory, Hai Nguyen, Tucker R. Balch, Char...
IJCAI
2007
15 years 5 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans