—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
Preferences in constraint problems are common but significant in many real world applications. In this paper, we extend our conditional and composite CSP (CCCSP) framework, managi...
Subcellular localization is a key functional characteristic of proteins. An automatic, reliable and efficient prediction system for protein subcellular localization is needed for ...
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...