Localized Multiple Kernel Learning---A Convex Approach

no code implementations • 14 Jun 2015 • Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft

We propose a localized approach to multiple kernel learning that can be formulated as a convex optimization problem over a given cluster structure.

Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms

no code implementations • NeurIPS 2015 • Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft

This paper studies the generalization performance of multi-class classification algorithms, for which we obtain, for the first time, a data-dependent generalization error bound with a logarithmic dependence on the class size, substantially improving the state-of-the-art linear dependence in the existing data-dependent generalization analysis.

General Classification Generalization Bounds +1

Extensions of stability selection using subsamples of observations and covariates

no code implementations • 18 Jul 2014 • Andre Beinrucker, Ürün Dogan, Gilles Blanchard

We introduce extensions of stability selection, a method to stabilise variable selection methods introduced by Meinshausen and B\"uhlmann (J R Stat Soc 72:417-473, 2010).

Variable Selection

Coordinate Descent with Online Adaptation of Coordinate Frequencies

no code implementations • 15 Jan 2014 • Tobias Glasmachers, Ürün Dogan

Coordinate descent (CD) algorithms have become the method of choice for solving a number of optimization problems in machine learning.

BIG-bench Machine Learning General Classification +1