Integration of multiple heterogeneous data sources continues to be a critical problem for many application domains and a challenge for researchers world-wide. With the increasing ...
In this paper, our main contribution is a framework for the automatic configuration of any spectral dimensionality reduction methods. This is achieved, first, by introducing the m...
Michal Lewandowski, Dimitrios Makris, Jean-Christo...
Recent years have seen considerable developments in modeling techniques for automatic fault location in programs. However, much of this research considered the models from a standa...
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...