We present an analysis and algorithm for the problem of super-resolution imaging, that is the reconstruction of HR (high-resolution) images from a sequence of LR (lowresolution) im...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Data sources on the web are often accessible through web interfaces that present them as relational tables, but require certain attributes to be mandatorily selected, e.g., via a w...
XML query languages typically allow the specification of structural patterns of elements. Finding the occurrences of such patterns in an XML tree is the key operation in XML quer...