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» Approximate Learning of Dynamic Models
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AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
15 years 12 months ago
Facial Expression Analysis Using Nonlinear Decomposable Generative Models
We present a new framework to represent and analyze dynamic facial motions using a decomposable generative model. In this paper, we consider facial expressions which lie on a one d...
Chan-Su Lee, Ahmed M. Elgammal
BC
2002
193views more  BC 2002»
15 years 6 months ago
Resonant spatiotemporal learning in large random recurrent networks
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Emmanuel Daucé, Mathias Quoy, Bernard Doyon
INTERSPEECH
2010
15 years 1 months ago
Binary coding of speech spectrograms using a deep auto-encoder
This paper reports our recent exploration of the layer-by-layer learning strategy for training a multi-layer generative model of patches of speech spectrograms. The top layer of t...
Li Deng, Michael L. Seltzer, Dong Yu, Alex Acero, ...
EH
2005
IEEE
158views Hardware» more  EH 2005»
15 years 12 months ago
Co-evolutionary Variance Can Guide Physical Testing in Evolutionary System Identification
Co-evolution of system models and system tests can be used for exploratory system identification of physical platforms. Here we demonstrate how the amount of physical testing can ...
Viktor Zykov, Josh C. Bongard, Hod Lipson
ICMLA
2008
15 years 7 months ago
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
Silvia Chiappa