The self-organizing map (SOM), a biologically inspired, learning algorithm from the field of artificial neural networks, is presented as a self-organized critical (SOC) model of the extremal dynamics family. The SOM's ability to converge to an ordered configuration, independent of the initial state, is known and has been demonstrated, in the one-dimensional case. In this ordered configuration it is now indicated by analysis and shown by simulation that the dynamics of the SOM are critical. By viewing the SOM as a SOC system, alternative interpretations of learning, the organized configuration, and the formation of topographic maps can be made.
Abstract. Mobile phones are often regarded as difficult to use due to their size restrictions. To improve on this, in this paper we described our approach using unsupervised learning to automate common tasks on a mobile phone, thereby requiring less key presses, by means of context-dependent quick-access shortcuts presented in the homescreen of the phone. We also briefly reviewed some of our user study findings, and raised the issue of possible privacy concerns with our implementation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.