Keynote Speakers
The stability of Factor Models of Interests rates
Brownian movement in gamma fields
Biological Aggregation at the Interface Between Theory and Practice To understand evolutionary processes better, biologists use aggregation methods to estimate evolutionary relationships; yet properties of the methods are sometimes so imprecisely defined, and their interrelationships so poorly understood, that useful formal results may be difficult to obtain. To address this problem I describe a strategy for modeling aggregation methods and studying their properties. Although motivated by biological problems, the strategy and its conceptual framework are generally applicable in research areas where aggregation problems arise.
Tests de Cramér-von Mises multivariés
The Entire Regularization Path for the Support Vector Machine The Support Vector Machine is a widely used tool for classification. Many efficient implementations exist for fitting a two-class SVM model. The user has to supply values for the tuning parameters: the regularization cost parameter, and the kernel parameters. It seems a common practice is to use a default value for the cost parameter, often leading to the least restrictive model. In this paper we argue that the choice of the cost parameter can be critical. We then derive an algorithm that can fit the entire path of SVM solutions for every value of the cost parameter, with essentially the same computational cost as fitting one SVM model. We illustrate our algorithm on some examples, and use our representation to give further insight into the range of SVM solutions. |