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ICASSP
2011
IEEE
14 years 7 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...
CCE
2006
15 years 3 months ago
Bayesian-based on-line applicability evaluation of neural network models in modeling automotive paint spray operations
The neural network (NN) models well trained and validated by the same data may exhibit noticeably different predictabilities in applications. This is mainly due to the fact that t...
Jia Li, Yinlun Huang
EOR
2006
73views more  EOR 2006»
15 years 3 months ago
Path relinking and GRG for artificial neural networks
Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is appr...
Abdellah El-Fallahi, Rafael Martí, Leon S. ...
JSW
2010
83views more  JSW 2010»
15 years 2 months ago
Estimating Model Parameters of Conditioned Soils by using Artificial Network
—The parameter identification of nonlinear constitutive model of soil mass is based on an inverse analysis procedure, which consists of minimizing the objective function represen...
Zichang Shangguan, Shouju Li, Wei Sun, Maotian Lua...
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 4 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi