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» Neural methods for non-standard data
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CANDC
2009
ACM
15 years 10 months ago
A sub-symbolic model of the cognitive processes of re-representation and insight
We present a sub-symbolic computational model for effecting knowledge re-representation and insight. Given a set of data, manifold learning is used to automatically organize the d...
Dan Ventura
BMCBI
2010
152views more  BMCBI 2010»
15 years 4 months ago
Comparative study of three commonly used continuous deterministic methods for modeling gene regulation networks
Background: A gene-regulatory network (GRN) refers to DNA segments that interact through their RNA and protein products and thereby govern the rates at which genes are transcribed...
Martin T. Swain, Johannes J. Mandel, Werner Dubitz...
IJCNN
2008
IEEE
15 years 10 months ago
Semi-supervised nearest neighbor editing
—This paper proposes a novel method for data editing. The goal of data editing in instance-based learning is to remove instances from a training set in order to increase the accu...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Sungyoun...
IPMI
1999
Springer
16 years 4 months ago
MEG Source Imaging Using Multipolar Expansions
We describe the use of truncated multipolar expansions for producing dynamic images of cortical neural activation from measurements of the magnetoencephalogram. We use a signal-sub...
John C. Mosher, Richard M. Leahy, David W. Shattuc...
IJCNN
2000
IEEE
15 years 7 months ago
Competing Hidden Markov Models on the Self-Organizing Map
This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
Panu Somervuo