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ICPR
2006
IEEE
16 years 29 days ago
Identification of degraded traffic sign symbols by a generative learning method
We present a novel training method for recognizing traffic sign symbols undergoing image degradations. In order to cope with the degradations, it is desirable to use similarly deg...
Hiroshi Murase, Hiroyuki Ishida, Ichiro Ide, Tomok...
SIGIR
2009
ACM
15 years 6 months ago
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
Reciprocal Rank Fusion (RRF), a simple method for combining the document rankings from multiple IR systems, consistently yields better results than any individual system, and bett...
Gordon V. Cormack, Charles L. A. Clarke, Stefan B&...
BMCBI
2010
109views more  BMCBI 2010»
14 years 12 months ago
Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
Background: In the last decade, biochemical studies have revealed that epigenetic modifications including histone modifications, histone variants and DNA methylation form a comple...
Xiaojiang Xu, Stephen Hoang, Marty W. Mayo, Stefan...
BMCBI
2007
153views more  BMCBI 2007»
14 years 12 months ago
Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis
Background: A nanopore detector has a nanometer-scale trans-membrane channel across which a potential difference is established, resulting in an ionic current through the channel ...
Matthew Landry, Stephen Winters-Hilt
ICML
2006
IEEE
16 years 20 days 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...