We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical ...
In this paper, we give an overview on some algorithms for learning automata. Starting with Biermann's and Angluin's algorithms, we describe some of the extensions caterin...
This paper is a continuation of the study of topological properties of omega context free languages (-CFL). We proved in [Topological Properties of Omega Context Free Languages, T...
Motivation Protein remote homology prediction and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines a...
We show that every NP problem is polynomially equivalent to a simple combinatorial problem: the membership problem for a special class of digraphs. These classes are defined by me...