We present an efficient method that computes dense stereo correspondences by stochastically sampling match quality values. Nonexhaustive sampling facilitates the use of quality met...
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
We investigate the implications of the conventional "t+2D" MC 3D-DWT structure for spatial scalability, and propose a more exible "2D+t+2D" structure. An initi...
We consider the problem of large scale retrieval evaluation. Recently two methods based on random sampling were proposed as a solution to the extensive effort required to judge te...