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» Modeling UCS as a mixture of experts
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TSMC
2008
109views more  TSMC 2008»
14 years 9 months ago
Analysis of CCME: Coevolutionary Dynamics, Automatic Problem Decomposition, and Regularization
In most real-world problems, we either know little about the problems or the problems are too complex to have a clear vision on how to decompose them by hand. Thus, it is usually d...
Minh Ha Nguyen, Hussein A. Abbass, Robert I. McKay

Publication
404views
15 years 6 months ago
Bayesian variable order Markov models.
We present a simple, effective generalisation of variable order Markov models to full online Bayesian estimation. The mechanism used is close to that employed in context tree wei...
Christos Dimitrakakis
NIPS
2004
14 years 10 months ago
Hierarchical Distributed Representations for Statistical Language Modeling
Statistical language models estimate the probability of a word occurring in a given context. The most common language models rely on a discrete enumeration of predictive contexts ...
John Blitzer, Kilian Q. Weinberger, Lawrence K. Sa...
ICASSP
2009
IEEE
15 years 4 months ago
Multi-view tracking of articulated human motion in silhouette and pose manifolds
This paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through Gaussian process latent variable model. The dime...
Feng Guo, Gang Qian
NN
2010
Springer
225views Neural Networks» more  NN 2010»
14 years 7 months ago
Learning to imitate stochastic time series in a compositional way by chaos
This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
Jun Namikawa, Jun Tani