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NIPS
1997
13 years 10 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
CAS
2007
87views more  CAS 2007»
13 years 8 months ago
An Accelerated Algorithm for Density Estimation in Large Databases Using Gaussian Mixtures
Today, with the advances of computer storage and technology, there are huge datasets available, offering an opportunity to extract valuable information. Probabilistic approaches ...
Alvaro Soto, Felipe Zavala, Anita Araneda
WOA
2007
13 years 10 months ago
Expectations driven approach for Situated, Goal-directed Agents
Abstract— Situated agents engaged in open systems continually face with external events requiring adequate services and behavioral responses. In these conditions agents should be...
Michele Piunti, Cristiano Castelfranchi, Rino Falc...
EMNLP
2011
12 years 8 months ago
Class Label Enhancement via Related Instances
Class-instance label propagation algorithms have been successfully used to fuse information from multiple sources in order to enrich a set of unlabeled instances with class labels...
Zornitsa Kozareva, Konstantin Voevodski, Shang-Hua...
ICCV
2011
IEEE
12 years 8 months ago
Shape-constrained Gaussian Process Regression for Facial-point-based Head-pose Normalization
Given the facial points extracted from an image of a face in an arbitrary pose, the goal of facial-point-based headpose normalization is to obtain the corresponding facial points ...
Ognjen Rudovic, Maja Pantic