Incremental Multi-Dimensional Scaling

Online Discovery of Feature Dependencies

Online representational expansion techniques have improved the learning speed of existing reinforcement learning (RL) algorithms in low dimensional domains, yet existing online expansion methods do not scale well to high dimensional problems. We conjecture that one of the main difficulties limiting this scaling is that features defined over the full-dimensional state space often generalize poor...

A Multi-Scaling Forward-Backward Time-Stepping Method for microwave imaging

This paper is aimed at presenting a new time-domain imaging technique that combines the regularization properties of the Filtered FBTS method with an efficient information-acquisition strategy, namely the Iterative Multi-Scaling Approach (IMSA). The proposed time-domain approach is then validated by means of a set of preliminary numerical test cases aimed at pointing out its features and potent...

NAVIGATION IN CYBERSPACE Using Multi-Dimensional Scaling to create three-dimensional navigational maps

This paper presents results regarding the performance of multidimensional scaling (MDS) when used to create three-dimensional navigation maps. MDS aims at reducing high-dimensional space into low-dimensional landscapes. Combined with browsers which are capable of visualizing threedimensional object information by applying the conceptual basis of Virtual Reality Modeling Language (VRML), MDS ope...

Using Trajectory Mapping to Analyze Musical Intervals

Cognitive scientists have often pondered the question of perceptual spaces, that is, the question of how a certain gamut of familiar stimuli might be organized in the mind. We present Trajectory Mapping as an alternative clustering method to the traditional algorithm of Multi-Dimensional Scaling. We suggest that given data about the relationships among stimuli, Multi-Dimensional Scaling provide...

Multi-Dimensional Scaling Assignment ‘Non-metric multidimensional scaling on data from the USA Beer Market’