137 search results - page 6 / 28 » Quantifying the Impact of Learning Algorithm Parameter Tunin... |
140
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ICANN
2005
Springer
15 years 7 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...
ICASSP
2011
IEEE
14 years 5 months ago
2011
IEEE
Constrained discriminative linear transform (CDLT) optimized with Extended Baum-Welch (EBW) has been presented in the literature as a discriminative speaker adaptation method that...
102
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SIGCOMM
1997
ACM
15 years 6 months ago
1997
ACM
— Measurement-based admission control (MBAC) is an attractive mechanism to concurrently offer quality of service (QoS) to users, without requiring a priori traffic specificatio...
127
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EUSFLAT
2003
15 years 3 months ago
2003
In this paper, an architecture of a resourceallocating learning probabilistic neural network is considered. Construction and learning algorithms are proposed. The advantages of th...
77
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ICML
2009
IEEE
16 years 2 months ago
2009
IEEE
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...