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» Computational Techniques for Modelling Learning in Economics
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COLT
1993
Springer
15 years 3 months ago
Parameterized Learning Complexity
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...
ACL
2012
13 years 2 months ago
Learning High-Level Planning from Text
Comprehending action preconditions and effects is an essential step in modeling the dynamics of the world. In this paper, we express the semantics of precondition relations extrac...
S. R. K. Branavan, Nate Kushman, Tao Lei, Regina B...
ATAL
2006
Springer
15 years 3 months ago
A hierarchical approach to efficient reinforcement learning in deterministic domains
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
CVPR
2004
IEEE
16 years 1 months ago
A Graphical Model Framework for Coupling MRFs and Deformable Models
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
WSDM
2010
ACM
254views Data Mining» more  WSDM 2010»
15 years 9 months ago
Learning Influence Probabilities In Social Networks
Recently, there has been tremendous interest in the phenomenon of influence propagation in social networks. The studies in this area assume they have as input to their problems a ...
Amit Goyal 0002, Francesco Bonchi, Laks V. S. Laks...