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This paper focuses on a class of zero-norm composite optimization problems. For this class of nonconvex nonsmooth problems, we establish the Kurdyka-Lojasiewicz property of exponent being a half for its objective function under a suitable…

Optimization and Control · Mathematics 2021-01-26 Yuqia Wu , Shaohua Pan , Shujun Bi

A formalized and quantifiable responsibility score is a crucial component in many aspects of the development and application of multi-agent systems and autonomous agents. We can employ it to inform decision making processes based on ethical…

Computer Science and Game Theory · Computer Science 2022-09-16 Sarah Hiller , Jonas Israel , Jobst Heitzig

This paper provides a semiparametric model of estimating states of the volatility defined as the squared diffusion coefficient of a stochastic differential equation. Without assuming any functional form of the volatility function, we…

Statistics Theory · Mathematics 2007-07-18 I. Shoji

Optimization under uncertainty and risk is indispensable in many practical situations. Our paper addresses stability of optimization problems using composite risk functionals which are subjected to measure perturbations. Our main focus is…

Optimization and Control · Mathematics 2022-01-06 Darinka Dentcheva , Yang Lin , Spiridon Penev

In this research, starting from a widely accepted definition of risk, we support the idea that risk reduction is a more realistic objective than risk minimization, which represents a theoretical utopia. Furthermore, significant risk…

Risk Management · Quantitative Finance 2026-05-01 Pierpaolo Uberti

Dimensionality reduction represents the process of generating a low dimensional representation of high dimensional data. Motivated by the formation control of mobile agents, we propose a nonlinear dynamical system for dimensionality…

Machine Learning · Computer Science 2025-01-17 Taeuk Jeong , Yoon Mo Jung , Euntack Lee

Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modelling of complex structural relationships. However, they are not commonly used in practice due to the need for…

Econometrics · Economics 2019-10-08 Victor Chernozhukov , Iván Fernández-Val , Whitney Newey , Sami Stouli , Francis Vella

We introduce the notion of modular forms, focusing primarily on the group PSL2Z. We further introduce quasi-modular forms, as wel as discuss their relation to physics and their applications in a variety of enumerative problems. These notes…

Number Theory · Mathematics 2014-07-07 Simon Rose

We develop a general mathematical framework for variational problems where the unknown function assumes values in the space of probability measures on some metric space. We study weak and strong topologies and define a total variation…

Numerical Analysis · Mathematics 2018-06-12 Thomas Vogt , Jan Lellmann

This paper studies the question of filtering and maximizing terminal wealth from expected utility in a partially information stochastic volatility models. The special features is that the only information available to the investor is the…

Portfolio Management · Quantitative Finance 2015-07-28 Dalia Ibrahim , Frédéric Abergel

The derivative expansion of the effective action is considered in the model with two interacting real scalar fields in curved spacetime. Using the functional approach and local momentum representation, the coefficient of the derivative term…

High Energy Physics - Theory · Physics 2025-07-01 Alícia G. Borges , Ilya L. Shapiro

An unsteady problem is considered for a space-fractional diffusion equation in a bounded domain. A first-order evolutionary equation containing a fractional power of an elliptic operator of second order is studied for general boundary…

Numerical Analysis · Computer Science 2014-12-19 Petr N. Vabishchevich

To be able to solve operator equations numerically a discretization of those operators is necessary. In the Galerkin approach bases are used to achieve discretized versions of operators. In a more general set-up, frames can be used to…

Functional Analysis · Mathematics 2016-12-20 Peter Balazs , Georg Rieckh

Classically, risk is characterized by a point value probability indicating the likelihood of occurrence of an adverse effect. However, there are domains where the attainability of objective numerical risk characterizations is increasingly…

Artificial Intelligence · Computer Science 2013-02-21 Paul J. Krause , John Fox , Philip Judson

We show how the separability problem is dual to that of decomposing any given matrix into a conic combination of rank-one partial isometries, thus offering a duality approach different to the positive maps characterization problem. Several…

Quantum Physics · Physics 2007-05-23 D. Salgado , J. L. Sanchez-Gomez , M. Ferrero

A general separability condition on the second moment (covariance matrix) for continuous variable two-party systems is derived by an analysis analogous to the derivation of the Kennard's uncertainty relation without referring to the…

Quantum Physics · Physics 2015-05-13 Kazuo Fujikawa

This article introduces probabilistic disjunctive normal forms (PDNFs) as a framework for representing and reasoning about uncertainty in logical systems. Unlike classical DNFs, PDNFs assign real-valued weights to variables, encoding…

Logic in Computer Science · Computer Science 2026-03-13 Alexander Kuznetsov

It is known that quaternions represent rotations in 3D Euclidean and Minkowski spaces. However, product by a quaternion gives rotation in two independent planes at once and to obtain single-plane rotations one has to apply by half-angle…

General Physics · Physics 2014-12-16 Merab Gogberashvili

The paper explores the differential inclusion of a special form. It is supposed that the support function of the set in the right-hand side of an inclusion may contain the sum of the maximum and the minimum of the finite number of…

Optimization and Control · Mathematics 2025-02-05 Alexander Fominyh

Recently, it has been emphasized that the possibility theory framework allows us to distinguish between i) what is possible because it is not ruled out by the available knowledge, and ii) what is possible for sure. This distinction may be…

Artificial Intelligence · Computer Science 2013-01-07 Salem Benferhat , Didier Dubois , Souhila Kaci , Henri Prade
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