Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
Automated extraction of structured data from Web sources often leads to large heterogeneous knowledge bases (KB), with data and schema items numbering in the hundreds of thousands...
Real-world datasets exhibit a complex dependency structure among the data attributes. Learning this structure is a key task in automatic statistics configuration for query optimi...
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...
Applications of the future will need to support large numbers of clients and will require scalable storage systems that allow state to be shared reliably. Recent research in distr...
Liuba Shrira, Barbara Liskov, Miguel Castro, Atul ...