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IWANN
2005
Springer
14 years 27 days 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
13 years 5 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»
13 years 8 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
13 years 8 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»
13 years 7 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