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NECO
2010
103views more  NECO 2010»
13 years 23 days ago
Population Models of Temporal Differentiation
Temporal derivatives are computed by a wide variety of neural circuits, but the problem of performing this computation accurately has received little theoretical study. Here we sy...
Bryan P. Tripp, Chris Eliasmith
NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 5 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
CEC
2007
IEEE
14 years 10 days ago
Improving generalization capability of neural networks based on simulated annealing
— This paper presents a single-objective and a multiobjective stochastic optimization algorithms for global training of neural networks based on simulated annealing. The algorith...
Yeejin Lee, Jong-Seok Lee, Sun-Young Lee, Cheol Ho...
TNN
2008
82views more  TNN 2008»
13 years 5 months ago
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
Cristiano Cervellera, Danilo Macciò, Marco ...
TNN
2011
132views more  TNN 2011»
13 years 14 days ago
Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals
—Prediction intervals (PIs) have been proposed in the literature to provide more information by quantifying the level of uncertainty associated to the point forecasts. Traditiona...
Abbas Khosravi, Saeid Nahavandi, Douglas C. Creigh...