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159
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CEC
2003
IEEE
15 years 9 months ago
Playing in continuous spaces: some analysis and extension of population-based incremental learning
- As an alternative to traditional Evolutionary Algorithms (EAs), Population-Based Incremental Learning (PBIL) maintains a probabilistic model of the best individual(s). Originally...
Bo Yuan, Marcus Gallagher
NN
2006
Springer
232views Neural Networks» more  NN 2006»
15 years 5 months ago
A probabilistic model of gaze imitation and shared attention
An important component of language acquisition and cognitive learning is gaze imitation. Infants as young as one year of age can follow the gaze of an adult to determine the objec...
Matthew W. Hoffman, David B. Grimes, Aaron P. Shon...
130
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ICML
2010
IEEE
15 years 6 months ago
Climbing the Tower of Babel: Unsupervised Multilingual Learning
For centuries, scholars have explored the deep links among human languages. In this paper, we present a class of probabilistic models that use these links as a form of naturally o...
Benjamin Snyder, Regina Barzilay

Book
778views
17 years 3 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 6 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava