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ACL
2007
13 years 6 months ago
A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
Feiyu Xu, Hans Uszkoreit, Hong Li
OOPSLA
2009
Springer
13 years 12 months ago
Towards automation of iteration planning
Iterations are time-boxed periods with an intended outcome that is often a set of implemented requirements. Iterations are part of most common software development lifecycle model...
Jonas Helming, Maximilian Koegel, Zardosht Hodaie
DIS
2009
Springer
13 years 12 months ago
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
CONTEXT
2007
Springer
13 years 11 months ago
Adaptive and Context-aware Scenarios for Technology Enhanced Learning System based on a Didactical Theory and a Hierarchical Tas
Among the main issues of future technology-enhanced learning systems, we can mention the following ones: the ability to reuse learning resources (learning objects, tools and servic...
Jean-Louis Tetchueng, Serge Garlatti, Sylvain Laub...
MICAI
2009
Springer
13 years 12 months ago
A Two-Stage Relational Reinforcement Learning with Continuous Actions for Real Service Robots
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
Julio H. Zaragoza, Eduardo F. Morales