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» On Combining Classifiers
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ICDAR
2009
IEEE
14 years 4 months ago
A Framework for Adaptation of the Active-DTW Classifier for Online Handwritten Character Recognition
: © A Framework for Adaptation of the Active-DTW Classifier for Online Handwritten Character Recognition Vandana Roy, Sriganesh Madhvanath, Anand S., Raghunath R. Sharma HP Labora...
Vandana Roy, Sriganesh Madhvanath, Anand S., Ragun...
ICML
2006
IEEE
14 years 11 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
14 years 4 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
ECCV
2008
Springer
15 years 1 hour ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele
ICPR
2006
IEEE
14 years 11 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum