Ordinal symbolic analysis and its application to biomedical recordings.

Is Human Atrial Fibrillation Stochastic or Deterministic?

Atrial fibrillation (AF) is the most common cardiac arrhythmia in human beings, and is associated with significant morbidity and mortality. The current standard of care includes interventional catheter ablation in selected patients, but the success rate is limited. The major limitation of the current approach to AF is the lack of fundamental understanding of its underlying mechanism. Specifical...

Detecting Change-Points in Time Series by Maximum Mean Discrepancy of Ordinal Pattern Distributions

As a new method for detecting change-points in high-resolution time series, we apply Maximum Mean Discrepancy to the distributions of ordinal patterns in different parts of a time series. The main advantage of this approach is its computational simplicity and robustness with respect to (non-linear) monotonic transformations, which makes it particularly well-suited for the analysis of long bioph...

Pursuing the Pareto Paradigm: Tournaments, Algorithm Variations & Ordinal Optimization

The ParetoGP algorithm which adopts a multi-objective optimization approach to balancing expression complexity and accuracy has proven to have significant impact on symbolic regression of industrial data due to its improvement in speed and quality of model development as well as user model selection, [1], [2], [3]. In this chapter, we explore a range of topics related to exploiting the Pareto p...

Recent advances in ordinal analysis: pi12 -- CA and related systems

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Ordinal and symbolic data analysis