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PKDD
2009
Springer
144views Data Mining» more  PKDD 2009»
14 years 4 months ago
Compositional Models for Reinforcement Learning
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Nicholas K. Jong, Peter Stone
PAMI
2002
112views more  PAMI 2002»
13 years 9 months ago
Recognizing Handwritten Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a nonlinear generative model of handwritten images of digits. The qua...
Guy Mayraz, Geoffrey E. Hinton
CORR
2006
Springer
102views Education» more  CORR 2006»
13 years 10 months ago
Structural Inference of Hierarchies in Networks
One property of networks that has received comparatively little attention is hierarchy, i.e., the property of having vertices that cluster together in groups, which then join to f...
Aaron Clauset, Cristopher Moore, M. E. J. Newman
ML
2006
ACM
187views Machine Learning» more  ML 2006»
13 years 10 months ago
Modeling, analyzing, and synthesizing expressive piano performance with graphical models
Abstract Trained musicians intuitively produce expressive variations that add to their audience's enjoyment. However, there is little quantitative information about the kinds ...
Graham Grindlay, David P. Helmbold
ICDM
2010
IEEE
193views Data Mining» more  ICDM 2010»
13 years 8 months ago
Supervised Link Prediction Using Multiple Sources
Link prediction is a fundamental problem in social network analysis and modern-day commercial applications such as Facebook and Myspace. Most existing research approaches this pro...
Zhengdong Lu, Berkant Savas, Wei Tang, Inderjit S....