222 search results - page 4 / 45 » Learning Optimal Parameters in Decision-Theoretic Rough Sets |
SIGECOM
2009
ACM
14 years 19 days ago
2009
ACM
The Target Set Selection problem proposed by Kempe, Kleinberg, and Tardos, gives a nice clean combinatorial formulation for many problems arising in economy, sociology, and medicin...
ICMCS
2007
IEEE
14 years 13 days 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...
ICML
2005
IEEE
14 years 7 months ago
2005
IEEE
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
AAAI
2006
13 years 7 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...
ICANN
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...