We propose a new strategy to estimate surface normal information from highly noisy sparse data. Our approach is based on a tensor field morphologically adapted to infer normals. I...
Marcelo Bernardes Vieira, Paulo P. Martins Jr., Ar...
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
In the process-algebraic veri cation of systems with three or more components put in parallel, alphabet axioms are considered to be very useful. These are rules that exploit the i...
This paper addresses a method of blind source separation that jointly exploits the nonstationarity and temporal structure of sources. The method needs only multiple time-delayed co...
In many applications, replacing a complex word form by its stem can reduce sparsity, revealing connections in the data that would not otherwise be apparent. In this paper, we focu...
Shane Bergsma, Aditya Bhargava, Hua He, Grzegorz K...