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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
FCS
2006
13 years 10 months ago
Algorithmic Control in Concurrent Computations
: In this paper, functioning and interaction of distributed devices and concurrent algorithms are analyzed in the context of the theory of algorithms. Although different systems in...
Mark Burgin
PDCN
2004
13 years 10 months ago
K-Means VQ algorithm using a low-cost parallel cluster computing
It is well-known that the time and memory necessary to create a codebook from large training databases have hindered the vector quantization based systems for real applications. T...
Paulo Sergio Lopes de Souza, Alceu de Souza Britto...
IPSN
2010
Springer
14 years 4 months ago
Consensus-based distributed linear support vector machines
This paper develops algorithms to train linear support vector machines (SVMs) when training data are distributed across different nodes and their communication to a centralized no...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...
ICA
2012
Springer
12 years 4 months ago
New Online EM Algorithms for General Hidden Markov Models. Application to the SLAM Problem
In this contribution, new online EM algorithms are proposed to perform inference in general hidden Markov models. These algorithms update the parameter at some deterministic times ...
Sylvain Le Corff, Gersende Fort, Eric Moulines