Asymptotic minimax estimators of a positive extreme value index under zero-one loss are investigated in the classical i.i.d. setup. To this end, we prove the weak convergence of suitable local experiments with Pareto distributions as center of localization to a white noise model, which was previously studied in the context of nonparametric local density estimation and regression. From this resu...

We use game theory to analyze meta-learning algorithms. The objective of meta-learning is to determine which algorithm to apply on a given task. This is an instance of a more general problem that consists of allocating knowledge consumers to learning producers. Solving this general problem in the field of meta-learning yields solutions for related fields such as information retrieval and recomm...

The Value is a solution concept originally due to Shapley (1953). The idea behind the concept is to evaluate how much will a player be willing to pay to participate in a given game. It seeks to represent what the game is worth for a player. In some sense the value captures the expected outcome of the game. We will start with the TU (transferable utility) framework and the axiomatic approach and...

While a wealth of statutory and auditing pronouncements attest to the importance of the auditing of journal entries for preventing and detecting material misstatements to financial statements, existing literature has so far paid inadequate attention to this line of research. To explore this line of research further, this paper proposes a bipartite model that is based on extreme value theory and...

Extreme value theory has emerged as one of the most important statistical disciplines for the applied sciences. Extreme value techniques are also becoming widely used in many other disciplines. For example, for portfolio adjustment in the insurance industry; for risk assessment on financial markets; and for traffic prediction in telecommunications. Here we do some basic data analysis in extreme...

We consider discrete time dynamical system and show the link between Hitting Time Statistics (the distribution of the first time points land in asymptotically small sets) and Extreme Value Theory (distribution properties of the partial maximum of stochastic processes). This relation allows to study Hitting Time Statistics with tools from Extreme Value Theory, and vice versa. We apply these resu...

The robustness of neural networks to adversarial examples has received great attention due to security implications. Despite various attack approaches to crafting visually imperceptible adversarial examples, little has been developed towards a comprehensive measure of robustness. In this paper, we provide a theoretical justification for converting robustness analysis into a local Lipschitz cons...

This paper argues that the notion of value has been overly simplified and narrowed to focus on economic retums. Stakeholder theory provides an appropriate lens for considering a more complex perspective of the value that stakeholders seek as well as new ways to measure it. We develop a four-factor perspective for defining value that includes, but extends beyond, the economic value stakeholders ...

We discuss the expectancy-value theory of motivation, focusing on an expectancy-value model developed and researched by Eccles, Wigfield, and their colleagues. Definitions of crucial constructs in the model, including ability beliefs, expectancies for success, and the components of subjective task values, are provided. These definitions are compared to those of related constructs, including sel...