We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
We present a family of methods for speeding up distributed locks by exploiting the uneven distribution of both temporal and spatial locality of access behaviour of many applicatio...
— Since the advent of distributed computer systems an active field of research has been the investigation of scheduling strategies for parallel applications. The common approach...
We show how to partition data structures representable by directed acyclic graphs, i.e. rooted trees, to allow for efficient complex operations, which lie beyond inserts, deletes ...