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AI
2011
Springer
13 years 5 months ago
Learning qualitative models from numerical data
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Dem...
AIED
2011
Springer
13 years 1 months ago
Causal Modeling of User Data from a Math Learning Environment with Game-Like Elements
We have created a math learning environment with game-like elements such as narrative, visual feedback, personalization, collection, etc. We made a study with four different versio...
Dovan Rai, Joseph E. Beck
MICCAI
2007
Springer
14 years 4 months ago
Robust Autonomous Model Learning from 2D and 3D Data Sets
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
ICONIP
2009
13 years 7 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
NIPS
1998
13 years 11 months ago
Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
This paper presents probabilistic modeling methods to solve the problem of discriminating between five facial orientations with very little labeled data. Three models are explored...
Shumeet Baluja