We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Every piece of textual data is generated as a method to convey its authors' opinion regarding specific topics. Authors deliberately organize their writings and create links, ...
Huajing Li, Zaiqing Nie, Wang-Chien Lee, C. Lee Gi...
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
: Covariance matrices capture correlations that are invaluable in modeling real-life datasets. Using all d2 elements of the covariance (in d dimensions) is costly and could result ...
Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...