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NCA
2002
IEEE
15 years 6 months ago
Comparison of Algorithmic and Machine Learning Approaches for the Automatic Fitting of Gaussian Peaks
Fitting gaussian peaks to experimental data is important in many disciplines, including nuclear spectroscopy. Nonlinear least squares fitting methods have been in use for a long t...
Radwan E. Abdel-Aal
DSMML
2004
Springer
15 years 12 months ago
Extensions of the Informative Vector Machine
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
ICML
2010
IEEE
15 years 7 months ago
Rectified Linear Units Improve Restricted Boltzmann Machines
Restricted Boltzmann machines were developed using binary stochastic hidden units. These can be generalized by replacing each binary unit by an infinite number of copies that all ...
Vinod Nair, Geoffrey E. Hinton
ECTEL
2006
Springer
15 years 10 months ago
Virtual Action Learning: Experiences from a Study of an SME e-Learning Programme
This paper presents the findings from a project investigating management development for SME managers using an action learning programme, combining both face-to-face workshops and ...
Jean-Anne Stewart, Gillian Alexander
BMCBI
2011
15 years 1 months ago
DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning
Background: Accurate identification of protein domain boundaries is useful for protein structure determination and prediction. However, predicting protein domain boundaries from a...
Jesse Eickholt, Xin Deng, Jianlin Cheng