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In this article, we present a new method to study uniqueness of form extensions in a rather general setting. The method is based on the theory of ordered Hilbert spaces and the concept of domination of semigroups. Our main abstract result…

Functional Analysis · Mathematics 2020-08-04 Daniel Lenz , Marcel Schmidt , Melchior Wirth

In this paper I consider all possible properties from commutative algebra for polynomial composites and monoid domains. The aim is full characterization of these structures. I start with the examination of group, ring, modules properties,…

Commutative Algebra · Mathematics 2020-06-29 Lukasz Matysiak

The density of states (DOS) is a spectral property of materials, which provides fundamental insights on various characteristics of materials. In this paper, we propose a model to predict the DOS by reflecting the nature of DOS: DOS…

Machine Learning · Computer Science 2023-04-11 Namkyeong Lee , Heewoong Noh , Sungwon Kim , Dongmin Hyun , Gyoung S. Na , Chanyoung Park

The binary radix expansion of a real number can be used to code the outcome of any series of coin tosses, a fact that provides an intriguing link between number theory, measure theory and statistical physics. Inspired by this fact, a…

Mathematical Physics · Physics 2020-03-11 Vladimir García-Morales , Javier Cervera , José A. Manzanares

We propose a discrete-time, finite-state stationary process that can possess long-range dependence. Among the interesting features of this process is that each state can have different long-term dependency, i.e., the indicator sequence can…

Probability · Mathematics 2022-09-19 Jeonghwa Lee

Stability of power networks is an increasingly important topic because of the high penetration of renewable distributed generation units. This requires the development of advanced (typically model-based) techniques for the analysis and…

Systems and Control · Computer Science 2018-09-14 T. W. Stegink , C. De Persis , A. J. van der Schaft

We propose a new network reliability measure for some particular kind of service networks, which we refer to as domination reliability. We relate this new reliability measure to the domination polynomial of a graph and the coverage…

Combinatorics · Mathematics 2025-12-03 Klaus Dohmen , Peter Tittmann

One version of the concept of structural controllability defined for single-input systems by Lin and subsequently generalized to multi-input systems by others, states that a parameterized matrix pair $(A, B)$ whose nonzero entries are…

Systems and Control · Computer Science 2019-11-12 Fengjiao Liu , A. Stephen Morse

We study the emergence of typicality in classical systems with a large number of binary state variables. We show analytically that for sufficiently large subsets of the complete state space, state functions which can be associated with…

Statistical Mechanics · Physics 2025-03-12 Nicolas Nessi

In the paper a new sufficient condition for the Aubin property to a class of parameterized variational systems is derived. In these systems the constraints depend both on the parameter as well as on the decision variable itself and they…

Optimization and Control · Mathematics 2018-10-31 Helmut Gfrerer , Jiri V. Outrata

From a research of several recent papers, in the first part, we are concerned with domination number in cubic graphs and give a sufficient condition of Reed's conjecture. In the second part, from a perspective, we study the structure of a…

Combinatorics · Mathematics 2018-03-20 Misa Nakanishi

In topics such as the thermodynamic formalism of linear cocycles, the dimension theory of self-affine sets, and the theory of random matrix products, it has often been found useful to assume positivity of the matrix entries in order to…

Dynamical Systems · Mathematics 2019-09-04 Balázs Bárány , Antti Käenmäki , Ian D. Morris

Stochastic dominance is an important concept in probability theory, econometrics and social choice theory for robustly modeling agents' preferences between random outcomes. While many works have been dedicated to the univariate case, little…

Machine Learning · Statistics 2024-06-11 Gabriel Rioux , Apoorva Nitsure , Mattia Rigotti , Kristjan Greenewald , Youssef Mroueh

Open dynamical systems are mathematical models of machines that take input, change their internal state, and produce output. For example, one may model anything from neurons to robots in this way. Several open dynamical systems can be…

Dynamical Systems · Mathematics 2016-02-25 David I. Spivak

The structure signature of a system made up of $n$ components having continuous and i.i.d. lifetimes was defined in the eighties by Samaniego as the $n$-tuple whose $k$-th coordinate is the probability that the $k$-th component failure…

Probability · Mathematics 2017-07-11 Jean-Luc Marichal , Pierre Mathonet , Jorge Navarro , Christian Paroissin

The nonlinear concepts of mixed summable families and maps for the spaces that only non-void sets are developed. Several characterizations of the corresponding concepts are achieved and the proof for a general Pietsch Domination-type…

Functional Analysis · Mathematics 2021-07-13 Salam Adel Al-Bayati , Akram Al-Sabbagh , Manaf Adnan Saleh Saleh

Submodular set-functions have many applications in combinatorial optimization, as they can be minimized and approximately maximized in polynomial time. A key element in many of the algorithms and analyses is the possibility of extending the…

Machine Learning · Computer Science 2016-02-24 Francis Bach

The dominated convergence theorem implies that if (f_n) is a sequence of functions on a probability space taking values in the interval [0,1], and (f_n) converges pointwise a.e., then the sequence of integrals converges to the integral of…

Functional Analysis · Mathematics 2014-01-03 Jeremy Avigad , Edward Dean , Jason Rute

In this paper, we provide an overview of the research conducted in the context of structural systems since the latest survey by Dion et al. in 2003. We systematically consider all the papers that cite this survey as well as the seminal work…

Optimization and Control · Mathematics 2020-08-27 Guilherme Ramos , A. Pedro Aguiar , Sergio Pequito

Transfer reinforcement learning aims to improve the sample efficiency of solving unseen new tasks by leveraging experiences obtained from previous tasks. We consider the setting where all tasks (MDPs) share the same environment dynamic…

Machine Learning · Computer Science 2021-01-08 Kaige Yang