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» On speaker adaptive training of artificial neural networks
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ICASSP
2011
IEEE
14 years 1 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
NIPS
1998
14 years 11 months ago
Controlling the Complexity of HMM Systems by Regularization
This paper introduces a method for regularization of HMM systems that avoids parameter overfitting caused by insufficient training data. Regularization is done by augmenting the E...
Christoph Neukirchen, Gerhard Rigoll
ESWA
2006
154views more  ESWA 2006»
14 years 9 months ago
Artificial neural networks with evolutionary instance selection for financial forecasting
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Kyoung-jae Kim
FLAIRS
2004
14 years 11 months ago
Backcalculation of Airport Flexible Pavement Non-Linear Moduli Using Artificial Neural Networks
The Heavy Weight Deflectometer (HWD) test is one of the most widely used tests for assessing the structural integrity of airport pavements in a non-destructive manner. The elastic...
Kasthurirangan Gopalakrishnan, Marshall R. Thompso...
CORR
2010
Springer
150views Education» more  CORR 2010»
14 years 9 months ago
Extraction of Symbolic Rules from Artificial Neural Networks
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
S. M. Kamruzzaman, Md. Monirul Islam