We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...
The use of genetic programming for probabilistic pattern matching is investigated. A stochastic regular expression language is used. The language features a statistically sound sem...
This paper proposes a gender recognition scheme focused on local appearance-based features to describe the top half of the face. Due to the fact that only the top half of the face ...
A novel, template-based method for face recognition is presented. The goals of the proposed method are to integrate multiple observations for improved robustness and to provide au...