Recent work has shown the importance of considering the adversary’s background knowledge when reasoning about privacy in data publishing. However, it is very difficult
for the d...
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Similarity metrics that are learned from labeled training
data can be advantageous in terms of performance
and/or efficiency. These learned metrics can then be used
in conjuncti...
In principle, the recovery and reconstruction of a 3D object from its 2D view projections require the parameterisation of its shape structure and surface re ectance properties. Exp...
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...