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EMNLP
2008
15 years 5 months ago
Learning with Probabilistic Features for Improved Pipeline Models
We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
Razvan C. Bunescu
JAIR
2002
120views more  JAIR 2002»
15 years 3 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
IJAR
2010
152views more  IJAR 2010»
15 years 2 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...
IS
2010
15 years 2 months ago
Identifying user strategies in exploratory learning with evolving task modelling
Abstract—In this paper we present work on adaptive identification of learners’ strategies, gradually developing a higher level of adaptation based on evolving models of mathem...
Mihaela Cocea, George D. Magoulas
TLT
2008
92views more  TLT 2008»
15 years 2 months ago
Lifelong Learner Modeling for Lifelong Personalized Pervasive Learning
Pervasive and ubiquitous computing has the potential to make huge changes in the ways that we will learn throughout our lives. This paper presents a vision for the lifelong user mo...
Judy Kay