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ICML
2009
IEEE
16 years 7 months ago
Robust feature extraction via information theoretic learning
In this paper, we present a robust feature extraction framework based on informationtheoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's...
Xiaotong Yuan, Bao-Gang Hu
ALT
2007
Springer
16 years 3 months ago
Learning Rational Stochastic Tree Languages
Abstract. We consider the problem of learning stochastic tree languages, i.e. probability distributions over a set of trees T(F), from a sample of trees independently drawn accordi...
François Denis, Amaury Habrard
ECCV
2010
Springer
15 years 9 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
CIARP
2008
Springer
15 years 9 months ago
Learning and Forgetting with Local Information of New Objects
The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to inco...
Fernando Vázquez, José Salvador S&aa...
IWEC
2007
15 years 8 months ago
Pass the Ball: Game-Based Learning of Software Design
Based on our experience using active learning methods to teach object-oriented software design we propose a game-based approach to take the classroom experience into a virtual envi...
Guillermo Jiménez-Díaz, Mercedes G&o...