Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
Abstract. This paper presents an architecture that enables the recognizer to learn incrementally and, thereby adapt to document image collections for performance improvement. We ar...
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
The objective of this study is to determine the right cycle management policy to service periodic soft real-time disk retrieval. Cycle based disk scheduling provides an effective ...
In this study, we propose an improved semi-supervised support vector machine (SVM) based translation algorithm for brain-computer interface (BCI) systems, aiming at reducing the t...