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RECOMB
2005
Springer
14 years 7 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
ICANN
2001
Springer
13 years 12 months ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
CVPR
2010
IEEE
14 years 3 months ago
Visual Event Recognition in Videos by Learning from Web Data
We propose a visual event recognition framework for consumer domain videos by leveraging a large amount of loosely labeled web videos (e.g., from YouTube). First, we propose a new...
Lixin Duan, Dong Xu, Wai-Hung Tsang, Jiebo Luo
BIBM
2010
IEEE
156views Bioinformatics» more  BIBM 2010»
13 years 5 months ago
Truncation of protein sequences for fast profile alignment with application to subcellular localization
We have recently found that the computation time of homology-based subcellular localization can be substantially reduced by aligning profiles up to the cleavage site positions of s...
Man-Wai Mak, Wei Wang, Sun-Yuan Kung
ICML
2009
IEEE
14 years 8 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou