We address the problem of efficiently gathering correlated data from a wireless sensor network, with the aim of designing algorithms with provable optimality guarantees, and unders...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Learning a discriminant becomes substantially more difficult when the datasets are high-dimensional and the available samples are few. This is often the case in computer vision an...
Santhosh Kodipaka, Arunava Banerjee, Baba C. Vemur...
In this paper we propose a novel inhomogeneous Gibbs model by the minimax entropy principle, and apply it to face modeling. The maximum entropy principle generalizes the statistic...
In this paper, we discuss new experiments on face recognition and authentication based on dimensional surface matching. While most of existing methods use facial intensity images,...