Recently, there has been a considerable research activity in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, the representational capabilities and internal representations of the models are not well understood. We rigorously analyze a generalization of the Self-Organizing Map (SOM) for processing sequential data, Recursive SOM (RecSOM [1]), as a non-autonomous dynamical system consisting off a set of fixed input maps. We show that contractive fixed input maps are likely to produce Markovian organizations of receptive fields o the RecSOM map. We derive bounds on parameter $\beta$ (weighting the importance of importing past information when processing sequences) under which co...
Models are abstractions of observed real world phenomena or processes. A good model captures the ess...
Self-organizing maps (SOMs) are widely used in several fields of application, from neurobiology to m...
We generalize a class of neural network models that extend the Kohonen Self-Organising Map (SOM) alg...
Recently, there has been a considerable research activity in extending topographic maps of vectorial...
Abstract. Recently, there has been a considerable research activity in extending topographic maps of...
Recently there has been an outburst of interest in extending topographic maps of vectorial data to m...
Recently, there has been an outburst of interest in extending topo-graphic maps of vectorial data to...
Recently, there has been an outburst of interest in extending topographic maps of vectorial data to ...
International audienceThis paper introduces representations and measurements for revealing the inner...
Self-organization constitutes an,important paradigm in machine learning with successful applications...
Self-organization constitutes an,important paradigm in machine learning with successful applications...
Self-organization constitutes an important paradigm in machine learning with successful app...
Self-organizing models constitute valuable tools for data visualization, clustering, and data mining...
Self-organizing models constitute valuable tools for data visualization, clustering, and data mining...
Abstract. We propose a self organizing map (SOM) for sequences by extending standard SOM by two feat...
Models are abstractions of observed real world phenomena or processes. A good model captures the ess...
Self-organizing maps (SOMs) are widely used in several fields of application, from neurobiology to m...
We generalize a class of neural network models that extend the Kohonen Self-Organising Map (SOM) alg...
Recently, there has been a considerable research activity in extending topographic maps of vectorial...
Abstract. Recently, there has been a considerable research activity in extending topographic maps of...
Recently there has been an outburst of interest in extending topographic maps of vectorial data to m...
Recently, there has been an outburst of interest in extending topo-graphic maps of vectorial data to...
Recently, there has been an outburst of interest in extending topographic maps of vectorial data to ...
International audienceThis paper introduces representations and measurements for revealing the inner...
Self-organization constitutes an,important paradigm in machine learning with successful applications...
Self-organization constitutes an,important paradigm in machine learning with successful applications...
Self-organization constitutes an important paradigm in machine learning with successful app...
Self-organizing models constitute valuable tools for data visualization, clustering, and data mining...
Self-organizing models constitute valuable tools for data visualization, clustering, and data mining...
Abstract. We propose a self organizing map (SOM) for sequences by extending standard SOM by two feat...
Models are abstractions of observed real world phenomena or processes. A good model captures the ess...
Self-organizing maps (SOMs) are widely used in several fields of application, from neurobiology to m...
We generalize a class of neural network models that extend the Kohonen Self-Organising Map (SOM) alg...