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ECTEL
2010
Springer
15 years 1 months ago
GVIS: A Facility for Adaptively Mashing Up and Representing Open Learner Models
In this article we present an infrastructure for creating mash up and visual representations of the user profile that combine data from different sources. We explored this approach...
Luca Mazzola, Riccardo Mazza
KDD
2007
ACM
170views Data Mining» more  KDD 2007»
16 years 4 months ago
From frequent itemsets to semantically meaningful visual patterns
Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....
Junsong Yuan, Ying Wu, Ming Yang
COLING
2008
15 years 5 months ago
Learning Reliable Information for Dependency Parsing Adaptation
In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...
Wenliang Chen, Youzheng Wu, Hitoshi Isahara
ICML
2003
IEEE
16 years 5 months ago
On Kernel Methods for Relational Learning
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
Chad M. Cumby, Dan Roth
ESANN
2003
15 years 5 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre