137 search results - page 1 / 28 » Quantifying the Impact of Learning Algorithm Parameter Tunin... |
AAAI
2006
13 years 6 months ago
2006
The impact of learning algorithm optimization by means of parameter tuning is studied. To do this, two quality attributes, sensitivity and classification performance, are investig...
ICMLA
2009
13 years 2 months ago
2009
This paper introduces a new algorithm, namely the EquiCorrelation Network (ECON), to perform supervised classification, and regression. ECON is a kernelized LARS-like algorithm, b...
HAIS
2008
Springer
13 years 6 months ago
2008
Springer
The widespread use of artificial neural networks and the difficult work regarding the correct specification (tuning) of parameters for a given problem are the main aspects that mot...
ICMCS
2007
IEEE
13 years 11 months ago
2007
IEEE
A common trait of background subtraction algorithms is that they have learning rates, thresholds, and initial values that are hand-tuned for a scenario in order to produce the des...
CP
2010
Springer
13 years 2 months ago
2010
Springer
The automatic tuning of the parameters of algorithms and automatic selection of algorithms has received a lot of attention recently. One possible approach is the use of machine lea...