Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from th...
Recent work in deduplication has shown that collective deduplication of different attribute types can improve performance. But although these techniques cluster the attributes col...
Both detection and tracking people are challenging problems, especially in complex real world scenes that commonly involve multiple people, complicated occlusions, and cluttered o...
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...