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IJCAI
1989
15 years 1 months ago
Using and Refining Simplifications: Explanation-Based Learning of Plans in Intractable Domains
This paper describes an explanation-based approach lo learning plans despite a computationally intractable domain theory. In this approach, the system learns an initial plan using...
Steve A. Chien
81
Voted
PRL
2008
91views more  PRL 2008»
15 years 19 days ago
Fuzzy relevance vector machine for learning from unbalanced data and noise
Handing unbalanced data and noise are two important issues in the field of machine learning. This paper proposed a complete framework of fuzzy relevance vector machine by weightin...
Dingfang Li, Wenchao Hu, Wei Xiong, Jin-Bo Yang
115
Voted
IJAR
2010
152views more  IJAR 2010»
14 years 11 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
120
Voted
APN
2010
Springer
14 years 10 months ago
Learning Workflow Petri Nets
Workflow mining is the task of automatically producing a workflow model from a set of event logs recording sequences of workflow events; each sequence corresponds to a use case or ...
Javier Esparza, Martin Leucker, Maximilian Schlund
ICC
2007
IEEE
133views Communications» more  ICC 2007»
15 years 7 months ago
Machine Learning for Automatic Defence Against Distributed Denial of Service Attacks
— Distributed Denial of Service attacks pose a serious threat to many businesses which rely on constant availability of their network services. Companies like Google, Yahoo and A...
Stefan Seufert, Darragh O'Brien