Supervised learning of a parts-based model can be for-
mulated as an optimization problem with a large (exponen-
tial in the number of parts) set of constraints. We show how
thi...
M. Pawan Kumar, Andrew Zisserman, Philip H.S. Torr
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
The manipulation of large-scale document data sets often involves the processing of a wealth of features that correspond with the available terms in the document space. The employm...
MOS (mean opinion score) subjective quality studies are used to evaluate many signal processing methods. Since laboratory quality studies are time consuming and expensive, researc...