It has been recently shown that, under the margin (or low noise) assumption, there exist classifiers attaining fast rates of convergence of the excess Bayes risk, that is, rates faster than n−1/2. The work on this subject has suggested the following two conjectures: (i) the best achievable fast rate is of the order n−1, and (ii) the plug-in classifiers generally converge more slowly than the cl...

We study large-scale classification problems in changing environments where a small part of the dataset is modified, and the effect of the data modification must be quickly incorporated into the classifier. When the entire dataset is large, even if the amount of the data modification is fairly small, the computational cost of re-training the classifier would be prohibitively large. In this pape...

A large volume of empirical research has accumulated on the relationship between religion/spirituality (R/S) and health since the year 2000, much of it involving older adults. The purpose of this article is to discuss how this body of existing research findings has important messages or important new insights for gerontologists; clinicians in medicine, psychiatry, and psychology; sociologists; ...

We study the recovery of sparse signals from underdetermined linear measurements when a potentially erroneous support estimate is available. Our results are twofold. First, we derive necessary and sufficient conditions for signal recovery from compressively sampled measurements using weighted l1norm minimization. These conditions, which depend on the choice of weights as well as the size and ac...

this paper develops an operational perspective of supply chain sustainability, by considering it as a risk management process. it explores the nature of sustainability-related supply chain risks, distinguishes them from typical supply chain risks and develops an analytical process for their management. an empirical study is conducted to generate insights about how sustainability-related risks s...

für Naturforschung in cooperation with the Max Planck Society for the Advancement of Science under a Creative Commons Attribution 4.0 International License. Dieses Werk wurde im Jahr 2013 vom Verlag Zeitschrift für Naturforschung in Zusammenarbeit mit der Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. digitalisiert und unter folgender Lizenz veröffentlicht: Creative Commons Namen...

I review recent efforts by political scientists and economists to explain crossnational variation in corruption using subjective ratings, and examine the robustness of reported findings. Quite strong evidence suggests that highly developed, long-established liberal democracies, with a free and widely read press, a high share of women in government, and a history of openness to trade are perceiv...

In this paper we calibrate the stationary Gaussian Musiela model to time series of market data using the Karhunen-Loeve expansion in order to get an ortonormal basis (classically known as EOF, empirical orthonormal functions) in a separable Hilbert space. The basis found is optimal for representing the covariance of the invariant measure of the forward rates’ process.

We introduce a framework for class noise, in which most of the known class noise models for the PAC setting can be formulated. Within this framework, we study properties of noise models that enable learning of concept classes of finite VC-dimension with the Empirical Risk Minimization (ERM) strategy. We introduce simple noise models for which classical ERM is not successful. Aiming at a more ge...

This Article is brought to you for free and open access by the Center for Coastal Physical Oceanography at ODU Digital Commons. It has been accepted for inclusion in CCPO Publications by an authorized administrator of ODU Digital Commons. For more information, please contact [email protected]. Repository Citation Oey, Lie-Yauw; Ezer, Tal; and Sturges, Wilton, "Modeled and Observed Empirica...