267 citations · 279 across the 3 of their papers we have counts for
4 papers
Fast rates for support vector machines using Gaussian kernels
Ingo Steinwart, Clint Scovel
For binary classification we establish learning rates up to the order of for support vector machines (SVMs) with hinge loss and Gaussian RBF kernels. These rates are in te…
Learning from dependent observations
Ingo Steinwart, Don Hush, Clint Scovel
In most papers establishing consistency for learning algorithms it is assumed that the observations used for training are realizations of an i.i.d. process. In this paper we go far…
A new concentration result for regularized risk minimizers
Ingo Steinwart, Don Hush, Clint Scovel
We establish a new concentration result for regularized risk minimizers which is similar to an oracle inequality. Applying this inequality to regularized least squares minimizers l…
Bayesian Stratified Sampling to Assess Corpus Utility
Judith Hochberg, Clint Scovel, Timothy Thomas +1
This paper describes a method for asking statistical questions about a large text corpus. We exemplify the method by addressing the question, "What percentage of Federal Register d…