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» On computational limitations of neural network architectures
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CVPR
2010
IEEE
14 years 4 months ago
Increasing depth resolution of Electron Microscopy of Neural circuits using Sparse Tomographic reconstruction
Future progress in neuroscience hinges on reconstruction of neuronal circuits to the level of individual synapses. Because of the specifics of neuronal architecture, imaging must ...
Ashok Veeraraghavan, Alex Genkin, Shiv Vitaladevun...
IMC
2007
ACM
13 years 9 months ago
Understanding the limitations of transmit power control for indoor wlans
A wide range of transmit power control (TPC) algorithms have been proposed in recent literature to reduce interference and increase capacity in 802.11 wireless networks. However, ...
Vivek Shrivastava, Dheeraj Agrawal, Arunesh Mishra...
IJCNN
2007
IEEE
14 years 1 months ago
TRUST-TECH Based Neural Network Training
— Efficient Training in a neural network plays a vital role in deciding the network architecture and the accuracy of these classifiers. Most popular local training algorithms t...
Hsiao-Dong Chiang, Chandan K. Reddy
EVOW
2010
Springer
14 years 2 months ago
Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions
DEODHAR, SUSHAMNA DEODHAR. Using Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions in Genetic Epidemiology. (Under the direction of Dr. Alison Motsinger-Re...
Sushamna Deodhar, Alison A. Motsinger-Reif
EUROCOLT
1997
Springer
13 years 11 months ago
Vapnik-Chervonenkis Dimension of Recurrent Neural Networks
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...
Pascal Koiran, Eduardo D. Sontag