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NECO
2006
47views more  NECO 2006»
13 years 11 months ago
A Maximum Likelihood Approach to Density Estimation with Semidefinite Programming
Tadayoshi Fushiki, Shingo Horiuchi, Takashi Tsuchi...
NECO
2006
71views more  NECO 2006»
13 years 11 months ago
Low-Dimensional Maps Encoding Dynamics in Entorhinal Cortex and Hippocampus
Dmitri D. Pervouchine, Theoden I. Netoff, Horacio ...
NECO
2006
56views more  NECO 2006»
13 years 11 months ago
Bayesian Population Decoding of Motor Cortical Activity Using a Kalman Filter
Wei Wu, Yun Gao, Elie Bienenstock, John P. Donoghu...
NECO
2006
111views more  NECO 2006»
13 years 11 months ago
Dynamics and Topographic Organization of Recursive Self-Organizing Maps
Recently, there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, at present, ...
Peter Tiño, Igor Farkas, Jort van Mourik
NECO
2006
61views more  NECO 2006»
13 years 11 months ago
A State-Space Analysis for Reconstruction of Goal-Directed Movements Using Neural Signals
Lakshminarayan Srinivasan, Uri T. Eden, Alan S. Wi...
NECO
2006
76views more  NECO 2006»
13 years 11 months ago
Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks
We study in this paper the effect of an unique initial stimulation on random recurrent networks of leaky integrate and fire neurons. Indeed given a stochastic connectivity this so...
Hédi Soula, Guillaume Beslon, Olivier Mazet
NECO
2006
157views more  NECO 2006»
13 years 11 months ago
Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression
The application of boosting technique to the regression problems has received relatively little attention in contrast to the research aimed at classification problems. This paper ...
Durga L. Shrestha, Dimitri P. Solomatine
NECO
2006
64views more  NECO 2006»
13 years 11 months ago
Implications of Neuronal Diversity on Population Coding
Maoz Shamir, Haim Sompolinsky
NECO
2006
60views more  NECO 2006»
13 years 11 months ago
On the Computational Power of Threshold Circuits with Sparse Activity
Circuits composed of threshold gates (McCulloch-Pitts neurons, or perceptrons) are simplified models of neural circuits with the advan1
Kei Uchizawa, Rodney J. Douglas, Wolfgang Maass