This paper investigates compression of 3D objects in computer graphics using manifold learning. Spectral compression uses the eigenvectors of the graph Laplacian of an object'...
This paper considers the problem of selecting the most informative experiments x to get measurements y for learning a regression model y = f(x). We propose a novel and simple conc...
Complex dialogs with comprehensive underlying data models are gaining increasing importance in today's Web applications. This in turn accelerates the need for highly dynamic ...
Patrick Freudenstein, Martin Nussbaumer, Florian A...
This paper studies the problem of unified ranked retrieval of heterogeneous XML documents and Web data. We propose an effective search engine called Sailer to adaptively and versa...
Conversation Clusters explores the use of visualization to highlight salient moments of live conversation while archiving a meeting. Cheaper storage and easy access to recording d...