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» An Instance Selection Approach to Multiple Instance Learning
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TSMC
2011
210views more  TSMC 2011»
14 years 4 months ago
Fault Diagnosis in Discrete-Event Systems: Incomplete Models and Learning
— Most state-based approaches to fault diagnosis of discrete-event systems require a complete and accurate model of the system to be diagnosed. In this paper, we address the prob...
Raymond H. Kwong, David L. Yonge-Mallo
APN
2010
Springer
14 years 8 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
ICTAI
2010
IEEE
14 years 7 months ago
Combining Learning Techniques for Classical Planning: Macro-operators and Entanglements
Planning techniques recorded a significant progress during recent years. However, many planning problems remain still hard even for modern planners. One of the most promising appro...
Lukás Chrpa
ICRA
2005
IEEE
118views Robotics» more  ICRA 2005»
15 years 3 months ago
Learning-Assisted Multi-Step Planning
— Probabilistic sampling-based motion planners are unable to detect when no feasible path exists. A common heuristic is to declare a query infeasible if a path is not found in a ...
Kris K. Hauser, Timothy Bretl, Jean-Claude Latombe
IJCNN
2006
IEEE
15 years 3 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang