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NIPS
2008
13 years 9 months ago
The Recurrent Temporal Restricted Boltzmann Machine
The Temporal Restricted Boltzmann Machine (TRBM) is a probabilistic model for sequences that is able to successfully model (i.e., generate nice-looking samples of) several very hi...
Ilya Sutskever, Geoffrey E. Hinton, Graham W. Tayl...

Publication
273views
12 years 5 months ago
 Beyond Graphs: A New Synthesis.
Artificial neural networks, electronic circuits, and gene networks are some examples of systems that can be modeled as networks, that is, as collections of interconnected nodes. I...
Mattiussi, Claudio, Dürr, Peter, Marbach, Daniel ...
VAMOS
2007
Springer
14 years 1 months ago
A Plea for Help with Variability, in Two Acts
A short theatrical exaggeration (but not too much) which describes practical problems with variability as experienced by real-world software developers. Real issue, there are no p...
Reed Little, Randy Blohm
ECCV
2006
Springer
14 years 9 months ago
Density Estimation Using Mixtures of Mixtures of Gaussians
In this paper we present a new density estimation algorithm using mixtures of mixtures of Gaussians. The new algorithm overcomes the limitations of the popular Expectation Maximiza...
Wael Abd-Almageed, Larry S. Davis
ICML
2003
IEEE
14 years 8 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...