Sciweavers

37 search results - page 2 / 8
» Parametric Kernels for Sequence Data Analysis
Sort
View
BICOB
2010
Springer
13 years 3 months ago
Multiple Kernel Learning for Fold Recognition
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...
Huzefa Rangwala
BMCBI
2008
145views more  BMCBI 2008»
13 years 5 months ago
Directed acyclic graph kernels for structural RNA analysis
Background: Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel ...
Kengo Sato, Toutai Mituyama, Kiyoshi Asai, Yasubum...
ICCV
1999
IEEE
14 years 7 months ago
Fluid Motion Recovery by Coupling Dense and Parametric Vector Fields
In this paper we address the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context standard motion estimation techniques ...
Étienne Mémin, Patrick Pérez
BIBM
2008
IEEE
125views Bioinformatics» more  BIBM 2008»
13 years 7 months ago
On the Role of Local Matching for Efficient Semi-supervised Protein Sequence Classification
Recent studies in protein sequence analysis have leveraged the power of unlabeled data. For example, the profile and mismatch neighborhood kernels have shown significant improveme...
Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic
NIPS
2008
13 years 6 months ago
Kernel Measures of Independence for non-iid Data
Many machine learning algorithms can be formulated in the framework of statistical independence such as the Hilbert Schmidt Independence Criterion. In this paper, we extend this c...
Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smo...