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EMNLP
2008
14 years 11 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
ICALT
2006
IEEE
15 years 4 months ago
Adaptive Learning Objects Sequencing for Competence-Based Learning
Lifelong learning refers to the activities people perform throughout their life to improve their competence in a particular field. Although adaptive educational hypermedia systems...
Pythagoras Karampiperis, Demetrios G. Sampson
JMLR
2010
172views more  JMLR 2010»
14 years 4 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....
TROB
2010
159views more  TROB 2010»
14 years 4 months ago
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives
Abstract--Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot learning. To be effective, action learning should not be limited to direct replic...
Ales Ude, Andrej Gams, Tamim Asfour, Jun Morimoto
ECAI
1990
Springer
15 years 1 months ago
Knowledge-Intensive Case-Based Reasoning and Sustained Learning
In case-based reasoning (CBR) a problem is solved by matching the problem description to a previously solved case, using the past solution in solving the new problem. A case-based...
Agnar Aamodt