− This paper proposes an automatic factorization method of the biological signals measured by Fluorescence Correlation Spectroscopy (FCS). Since the signals are composed from sev...
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
This paper deals with a blind deconvolution (DB) problem for multiple-input multiple-output infinite impulse response (MIMO-IIR) systems. To solve this problem, we propose an eige...
We proposed a neural segmentation model that is suitable for implementation in analog VLSIs using conventional CMOS technology. The model consists of neural oscillators mutually co...
Gessyca Maria Tovar, Eric Shun Fukuda, Tetsuya Asa...
There is no consensus on measuring distances between two different neural network architectures. Two folds of methods are used for that purpose: Structural and behavioral distance ...
Abstract. The paper describes the integration of brain-inspired systems to perform audiovisual pattern recognition tasks. Individual sensory pathways as well as the integrative mod...
Simei Gomes Wysoski, Lubica Benuskova, Nikola Kasa...
In this study we propose a new ensemble model composed of several linear perceptrons. The objective of this study is to build a piecewise-linear classifier that is not only compet...
In this paper, we discuss kernels that can be applied for the classification of XML documents based on their DOM trees. DOM trees are ordered trees in which every node might be la...
Peter Geibel, Olga Pustylnikov, Alexander Mehler, ...
Multiclass gene selection and classification of cancer are rapidly gaining attention in recent years, while conventional rank-based gene selection methods depend on predefined idea...