Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
Recent theoretical and empirical work in statistical machine learning has demonstrated the importance of learning algorithms for deep architectures, i.e., function classes obtaine...
In this paper, we propose a novel approach for learning generic visual vocabulary. We use diffusion maps to au-tomatically learn a semantic visual vocabulary from ab-undant quantiz...
Jingen Liu (University of Central Florida), Yang Y...
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...