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» Selection of Subsets of Ordered Features in Machine Learning
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ICML
2000
IEEE
16 years 4 months ago
Discovering Homogeneous Regions in Spatial Data through Competition
If all features causing heterogeneity were observed, a mixture of experts approach (Jacobs et al., 1991) is likely to be superior to using a single model. When unobserved or very n...
Slobodan Vucetic, Zoran Obradovic
KI
2007
Springer
15 years 3 months ago
Improving the Detection of Unknown Computer Worms Activity Using Active Learning
Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after t...
Robert Moskovitch, Nir Nissim, Dima Stopel, Clint ...
140
Voted
AIA
2007
15 years 5 months ago
Classification of biomedical high-resolution micro-CT images for direct volume rendering
This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipel...
Maite López-Sánchez, Jesús Ce...
BMCBI
2004
140views more  BMCBI 2004»
15 years 3 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard
ICML
2004
IEEE
16 years 4 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...