There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources -from sensor data, experimental data, data fro...
Our objective is transfer training of a discriminatively trained object category detector, in order to reduce the number of training images required. To this end we propose three ...
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
We introduce a new unsupervised fMRI analysis method based on Kernel Canonical Correlation Analysis which differs from the class of supervised learning methods that are increasing...
The recently developed i-vector framework for speaker recognition has set a new performance standard in the research field. An i-vector is a compact representation of a speaker u...