Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
Background: With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables ...
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Background: Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-ba...
Frederick A. Matsen III, Robin B. Kodner, E. Virgi...
Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the ...
Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Ja...