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» Constructing informative priors using transfer learning
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ICML
2006
IEEE
14 years 5 months ago
Constructing informative priors using transfer learning
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
Rajat Raina, Andrew Y. Ng, Daphne Koller
ICML
2007
IEEE
14 years 5 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
DAGM
2009
Springer
13 years 11 months ago
Learning with Few Examples by Transferring Feature Relevance
The human ability to learn difficult object categories from just a few views is often explained by an extensive use of knowledge from related classes. In this work we study the use...
Erik Rodner, Joachim Denzler
ECCV
2008
Springer
14 years 6 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
TVCG
2010
183views more  TVCG 2010»
13 years 3 months ago
Exploration and Visualization of Segmentation Uncertainty using Shape and Appearance Prior Information
—We develop an interactive analysis and visualization tool for probabilistic segmentation in medical imaging. The originality of our approach is that the data exploration is guid...
Ahmed Saad, Ghassan Hamarneh, Torsten Möller