Abstract. In many situations, high dimensional data can be considered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by appro...
Abstract. A well-known result by Stein shows that regularized estimators with small bias often yield better estimates than unbiased estimators. In this paper, we adapt this spirit ...
We propose an algorithm for recovering the matrix A in X = AS where X is a random vector of lower dimension than S. S is assumed to be sparse in the sense that S has less nonzero e...
Fabian J. Theis, Pando G. Georgiev, Andrzej Cichoc...
The one-dimensional functional equation g(y(t)) = cg(z(t)) with known functions y and z and constant c is considered. The indeterminacies are calculated, and an algorithm for appro...
Abstract. In most ICA algorithms, the separation performances are estimated through the evaluation of a contrast function , used in the update rule of elements of the unmixing matr...