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» Scalable, updatable predictive models for sequence data
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SASP
2009
IEEE
291views Hardware» more  SASP 2009»
14 years 2 months ago
A parameterisable and scalable Smith-Waterman algorithm implementation on CUDA-compatible GPUs
—This paper describes a multi-threaded parallel design and implementation of the Smith-Waterman (SM) algorithm on compute unified device architecture (CUDA)-compatible graphic pr...
Cheng Ling, Khaled Benkrid, Tsuyoshi Hamada
ESANN
2008
13 years 9 months ago
Survival SVM: a practical scalable algorithm
This work advances the Support Vector Machine (SVM) based approach for predictive modelling of failure time data as proposed in [1]. The main results concern a drastic reduction in...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
NIPS
2007
13 years 9 months ago
Predictive Matrix-Variate t Models
It is becoming increasingly important to learn from a partially-observed random matrix and predict its missing elements. We assume that the entire matrix is a single sample drawn ...
Shenghuo Zhu, Kai Yu, Yihong Gong
PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
14 years 2 months ago
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...
ICMLA
2008
13 years 9 months ago
Highly Scalable SVM Modeling with Random Granulation for Spam Sender Detection
Spam sender detection based on email subject data is a complex large-scale text mining task. The dataset consists of email subject lines and the corresponding IP address of the em...
Yuchun Tang, Yuanchen He, Sven Krasser