The statistical pattern recognition based on Bayes formula implies the concept of mutually exclusive classes. This assumption is not applicable when we have to identify some non-ex...
This paper presents an application of multiple kernels like Kernel Basis to the Relevance Vector Machine algorithm. The framework of kernel machines has been a source of many works...
The use of engineered nanopores as sensing elements for chemical and biological agents is a rapidly developing area. The distinct signatures of nanopore-nanoparticle lend themselve...
We propose to model human reasoning tasks using completed logic programs interpreted under the three-valued Lukasiewicz semantics. Given an appropriate immediate consequence operat...
Simbed, standing for similarity-based embedding, is a new method of embedding high-dimensional data. It relies on the preservation of pairwise similarities rather than distances. I...
Backpropagation of errors is not only hard to justify from biological perspective but also it fails to solve problems requiring complex logic. A simpler algorithm based on generati...
This work examines the dendritic cell algorithm (DCA) from a mathematical perspective. By representing the signal processing phase of the algorithm using the dot product it is sho...
Thomas Stibor, Robert Oates, Graham Kendall, Jonat...
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
Mathematical modeling for gene regulative networks (GRNs) provides an effective tool for hypothesis testing in biology. A necessary step in setting up such models is the estimati...
Indicator-based algorithms have become a very popular approach to solve multi-objective optimization problems. In this paper, we contribute to the theoretical understanding of alg...