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IWANN
2005
Springer
15 years 3 months ago
Input and Structure Selection for k-NN Approximator
Abstract. This paper presents k-NN as an approximator for time series prediction problems. The main advantage of this approximator is its simplicity. Despite the simplicity, k-NN c...
Antti Sorjamaa, Nima Reyhani, Amaury Lendasse
BMVC
2010
14 years 7 months ago
Local Gaussian Processes for Pose Recognition from Noisy Inputs
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Martin Fergie, Aphrodite Galata
NCI
2004
141views Neural Networks» more  NCI 2004»
14 years 11 months ago
Estimating the error at given test input points for linear regression
In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
Masashi Sugiyama
AAAI
2006
14 years 11 months ago
Automatically Labeling the Inputs and Outputs of Web Services
Information integration systems combine data from multiple heterogeneous Web services to answer complex user queries, provided a user has semantically modeled the service first. T...
Kristina Lerman, Anon Plangprasopchok, Craig A. Kn...
BIOSYSTEMS
2007
56views more  BIOSYSTEMS 2007»
14 years 9 months ago
Determination of the fraction of active inputs required by a neuron to fire
What fraction of the inputs to a neuron in the primary visual cortex (V1) need to be active for that neuron to reach its firing threshold? The paper describes a numerical method f...
Guido Bugmann