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» Learning a Generative Model for Structural Representations
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PRICAI
2000
Springer
13 years 11 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
IIE
2008
88views more  IIE 2008»
13 years 7 months ago
Development of Generative Learning Objects Using Feature Diagrams and Generative Techniques
Abstract. Learning Objects (LOs) play a key role for supporting eLearning. In general, however, the development of LOs remains a vague issue, because there is still no clearly defi...
Vytautas Stuikys, Robertas Damasevicius
ECCV
2002
Springer
14 years 9 months ago
Multimodal Data Representations with Parameterized Local Structures
Abstract. In many vision problems, the observed data lies in a nonlinear manifold in a high-dimensional space. This paper presents a generic modelling scheme to characterize the no...
Ying Zhu, Dorin Comaniciu, Stuart C. Schwartz, Vis...
ICML
2007
IEEE
14 years 8 months ago
Two-view feature generation model for semi-supervised learning
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Rie Kubota Ando, Tong Zhang
AAAI
2000
13 years 8 months ago
Modeling Classification and Inference Learning
Human categorization research is dominated by work in classification learning. The field may be in danger of equating the classification learning paradigm with the more general ph...
Bradley C. Love, Arthur B. Markman, Takashi Yamauc...