As high-end computing systems continue to grow in scale, recent advances in multiand many-core architectures have pushed such growth toward more denser architectures, that is, mor...
Pavan Balaji, Darius Buntinas, David Goodell, Will...
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
Since 2005, processor designers have increased core counts to exploit Moore’s Law scaling, rather than focusing on single-core performance. The failure of Dennard scaling, to wh...
In this paper, we present a large-scale object retrieval system. The user supplies a query object by selecting a region of a query image, and the system returns a ranked list of i...
James Philbin, Ondrej Chum, Michael Isard, Josef S...
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...