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» Boosting Methods for Regression
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CVPR
2010
IEEE
14 years 5 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
BMCBI
2010
106views more  BMCBI 2010»
13 years 10 months ago
TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays
Background: High-throughput genotyping microarrays assess both total DNA copy number and allelic composition, which makes them a tool of choice for copy number studies in cancer, ...
Henrik Bengtsson, Pierre Neuvial, Terence P. Speed
TKDE
2008
112views more  TKDE 2008»
13 years 9 months ago
IDD: A Supervised Interval Distance-Based Method for Discretization
This paper introduces a new method for supervised discretization based on interval distances by using a novel concept of neighborhood in the target's space. The proposed metho...
Francisco J. Ruiz, Cecilio Angulo, Núria Ag...
ICML
2006
IEEE
14 years 10 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
MP
2010
162views more  MP 2010»
13 years 8 months ago
Approximation accuracy, gradient methods, and error bound for structured convex optimization
Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...
Paul Tseng