Advances in the development of large scale distributed computing systems such as Grids and Computing Clouds have intensified the need for developing scheduling algorithms capable...
Claris Castillo, George N. Rouskas, Khaled Harfous...
Sampling methods are a direct approach to tackle the problem of class imbalance. These methods sample a data set in order to alter the class distributions. Usually these methods ar...
Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Mar...
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 ...
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
This paper proposes a data mining approach to modeling relationships among categories in image collection. In our approach, with image feature grouping, a visual dictionary is cre...