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...

Graduate students and postdoctoral fellows currently encounter requests for a statement of teaching philosophy in at least half of academic job announcements in the United States. A systematic process for the development of a teaching statement is required that integrates multiple sources of support, informs writers of the document's purpose and audience, helps writers produce thoughtful statem...

Abstract: Model selection is often performed by empirical risk minimization. The quality of selection in a given situation can be assessed by risk bounds, which require assumptions both on the margin and the tails of the losses used. Starting with examples from the 3 basic estimation problems, regression, classification and density estimation, we formulate risk bounds for empirical risk minimiz...

The Discrepancy Method is a constructive method for proving upper bounds that has received a lot of attention in recent years. In this paper we revisit a few important results, and show how it can be applied to problems in Machine Learning such as the Empirical Risk Minimization and Risk Estimation by exploiting connections with combinatorial dimension theory.

Water vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV) is urgently needed, but has long been constrained by data availability. Our study derived the vertically integrated precipitable water vapor over eas...

Despite the increasing evidence of drastic and profound changes in many ecosystems, often referred to as regime shifts, we have little ability to understand the processes that provide insurance against such change (resilience). Modelling studies have suggested that increased variance may foreshadow a regime shift, but this requires long-term data and knowledge of the functional links between ke...

We determine theoretically the relation between the total number of protons Np and the mass number A (the charge to mass ratio) of nuclei and neutron cores with the model recently proposed by Ruffini et al. (2007) and we compare it with other Np versus A relations: the empirical one, related to the Periodic Table, and the semi-empirical relation, obtained by minimizing the Weizsäcker mass formu...