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» A Composite Stabilizing Data Structure
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NECO
1998
119views more  NECO 1998»
13 years 7 months ago
Density Estimation by Mixture Models with Smoothing Priors
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
Akio Utsugi
MONET
2007
110views more  MONET 2007»
13 years 7 months ago
Multi-hop Clustering Based on Neighborhood Benchmark in Mobile Ad-hoc Networks
— Large-scale mobile ad-hoc networks require flexible and stable clustered network structure for efficient data collection and dissemination. In this paper, a scheme is present...
Stephen S. Yau, Wei Gao
CEC
2009
IEEE
14 years 2 months ago
Evolving hypernetwork models of binary time series for forecasting price movements on stock markets
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...
Elena Bautu, Sun Kim, Andrei Bautu, Henri Luchian,...
UAI
2003
13 years 9 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
BMCBI
2007
97views more  BMCBI 2007»
13 years 7 months ago
Relating destabilizing regions to known functional sites in proteins
Background: Most methods for predicting functional sites in protein 3D structures, rely on information on related proteins and cannot be applied to proteins with no known relative...
Benoit H. Dessailly, Marc F. Lensink, Shoshana J. ...