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103
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TNN
2008
177views more  TNN 2008»
15 years 19 days 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
102
Voted
IJCNN
2006
IEEE
15 years 6 months ago
Computational Neurogenetic Modeling: A Methodology to Study Gene Interactions Underlying Neural Oscillations
—We present new results from Computational Neurogenetic Modeling to aid discoveries of complex gene interactions underlying oscillations in neural systems. Interactions of genes ...
Lubica Benuskova, Simei Gomes Wysoski, Nikola K. K...
118
Voted
GANDC
2011
93views more  GANDC 2011»
14 years 12 days ago
Bayesian spatial modeling and interpolation using copulas
Copulas have attracted much attention in spatial statistics over the past few years. They are used as a flexible alternative to traditional methods for nonGaussian spatial modelin...
Hannes Kazianka, Jürgen Pilz
109
Voted
ICMCS
2007
IEEE
167views Multimedia» more  ICMCS 2007»
15 years 27 days ago
A Probability Model for Image Annotation
Automatic image annotation is a promising solution to enable more effective image retrieval by keywords. Traditionally, statistical models for image auto-annotation predicate each...
Yong Ge, Richang Hong, Zhiwei Gu, Rong Zhang, Xiuq...
CICLING
2010
Springer
15 years 7 months ago
A Sequential Model for Discourse Segmentation
Identifying discourse relations in a text is essential for various tasks in Natural Language Processing, such as automatic text summarization, question-answering, and dialogue gene...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...