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» Probabilistic Neural Network Models for Sequential Data
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JMLR
2012
11 years 10 months ago
Krylov Subspace Descent for Deep Learning
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
Oriol Vinyals, Daniel Povey
ESANN
2007
13 years 9 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
ACIVS
2007
Springer
14 years 2 months ago
Spatiotemporal Fusion Framework for Multi-camera Face Orientation Analysis
In this paper, we propose a collaborative technique for face orientation estimation in smart camera networks. The proposed spatiotemporal feature fusion analysis is based on active...
Chung-Ching Chang, Hamid K. Aghajan
CVPR
2000
IEEE
14 years 10 months ago
Recognizing Upper Face Action Units for Facial Expression Analysis
We develop an automatic system to analyze subtle changes in upper face expressions based on both permanent facial features (brows, eyes, mouth)andtransient facial features (deepen...
Ying-li Tian, Takeo Kanade, Jeffrey F. Cohn
NC
1998
13 years 9 months ago
An Addition to Backpropagation for Computing Functional Roots
Many processes are composed of a n-fold repetition of some simpler process. If the whole process can be modeled with a neural network, we present a method to derive a model of the...
Lars Kindermann