We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Abstract. While injecting weight noise during training has been proposed for more than a decade to improve the convergence, generalization and fault tolerance of a neural network, ...
Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a lowdimensional target space. Thereby, the distance relationshi...
Marc Strickert, Stefan Teichmann, Nese Sreenivasul...
The residual variance estimation problem is well-known in statistics and machine learning with many applications for example in the field of nonlinear modelling. In this paper, we...
Abstract— Independent subspace analysis (ISA) is a generalization of independent component analysis (ICA), where multidimensional ICA is incorporated with the idea of invariant f...