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JMLR
2010
206views more  JMLR 2010»
14 years 4 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
59
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ICML
2008
IEEE
15 years 10 months ago
Sequence kernels for predicting protein essentiality
The problem of identifying the minimal gene set required to sustain life is of crucial importance in understanding cellular mechanisms and designing therapeutic drugs. This work d...
Cyril Allauzen, Mehryar Mohri, Ameet Talwalkar
CSIE
2009
IEEE
15 years 4 months ago
Identifying DNA Strands Using a Kernel of Classified Sequences
— Automated DNA sequencing produces a large amount of raw DNA sequence data that then needs to be classified, organized, and annotation. One major application is the comparison o...
Guillermo Tonsmann, David D. Pollock, Wanjun Gu, T...
EUSFLAT
2009
132views Fuzzy Logic» more  EUSFLAT 2009»
14 years 7 months ago
Modeling Position Specificity in Sequence Kernels by Fuzzy Equivalence Relations
This paper demonstrates that several known sequence kernels can be expressed in a unified framework in which the position specificity is modeled by fuzzy equivalence relations. In ...
Ulrich Bodenhofer, Karin Schwarzbauer, Mihaela Ion...
BMCBI
2004
113views more  BMCBI 2004»
14 years 9 months ago
Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...