Abstract--Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), indepe...
We propose two new tools to address the evolution of hyperlinked corpora. First, we define time graphs to extend the traditional notion of an evolving directed graph, capturing li...
Ravi Kumar, Jasmine Novak, Prabhakar Raghavan, And...
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
Segmentation is one of the fundamental components in time series data mining. One of the uses of the time series segmentation is trend analysis - to segment the time series into pr...
In this paper, we provide a study of Max-Min Fair (MMF) multicommodity flows and focus on some of their applications to multi-commodity networks. We first present the theoretical ...