Sciweavers

147 search results - page 3 / 30
» Discriminative Training of a Neural Network Statistical Pars...
Sort
View
TNN
2008
177views more  TNN 2008»
13 years 6 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal
ESWA
2008
124views more  ESWA 2008»
13 years 6 months ago
A hybrid financial analysis model for business failure prediction
Accounting frauds have continuously happened all over the world. This leads to the need of predicting business failures. Statistical methods and machine learning techniques have b...
Shi-Ming Huang, Chih-Fong Tsai, David C. Yen, Yin-...
BMCBI
2007
141views more  BMCBI 2007»
13 years 6 months ago
Artificial neural network models for prediction of intestinal permeability of oligopeptides
Background: Oral delivery is a highly desirable property for candidate drugs under development. Computational modeling could provide a quick and inexpensive way to assess the inte...
Eunkyoung Jung, Junhyoung Kim, Minkyoung Kim, Dong...
COLING
1996
13 years 7 months ago
FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
Finn Dag Buø, Alex Waibel
BMCBI
2008
138views more  BMCBI 2008»
13 years 6 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones