Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
This paper proposes an improved particle swarm optimizer using the notion of species to determine its neighbourhood best values, for solving multimodal optimization problems. In th...
We describe some extensions to the grid smoothing scheme described in [1, 2] that deal with the following issues: 1) the clustering effect of changing valence in an unstructured ...
In this paper we describe how the Stepwise Adaptation of Weights (saw) technique can be applied in genetic programming. The saw-ing mechanism has been originally developed for and ...