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NN
1998
Springer
108views Neural Networks» more  NN 1998»
14 years 9 months ago
How embedded memory in recurrent neural network architectures helps learning long-term temporal dependencies
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
Tsungnan Lin, Bill G. Horne, C. Lee Giles
TITB
2002
172views more  TITB 2002»
14 years 9 months ago
Shape recovery algorithms using level sets in 2-D/3-D medical imagery: a state-of-the-art review
The class of geometric deformable models, also known as level sets, has brought tremendous impact to medical imagery due to its capability of topology preservation and fast shape r...
Jasjit S. Suri, Kecheng Liu, Sameer Singh, Swamy L...
ML
2007
ACM
156views Machine Learning» more  ML 2007»
14 years 9 months ago
Active learning for logistic regression: an evaluation
Which active learning methods can we expect to yield good performance in learning binary and multi-category logistic regression classifiers? Addressing this question is a natural ...
Andrew I. Schein, Lyle H. Ungar
CIKM
2010
Springer
14 years 8 months ago
Third workshop on exploiting semantic annotations in information retrieval (ESAIR): CIKM 2010 workshop
There is an increasing amount of structure on the Web as a result of modern Web languages, user tagging and annotation, and emerging robust NLP tools. These meaningful, semantic, ...
Jaap Kamps, Jussi Karlgren, Ralf Schenkel
MA
2010
Springer
172views Communications» more  MA 2010»
14 years 8 months ago
On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors
We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analy...
Vivekananda Roy, James P. Hobert