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In practice, it is not possible to observe a whole max-stable random field. Therefore, a way how to reconstruct a max-stable random field in $C\left([0,1]^k\right)$ by interpolating its realizations at finitely many points is proposed. The…

Probability · Mathematics 2017-03-13 Michael Falk , Maximilian Zott

In the ultraviolet (UV) scattering communication, the received signals exhibit the characteristics of discrete photoelectrons due to path loss. The synchronization is based on maximum Pulse Number-Sequence correlation problem. First of all,…

Signal Processing · Electrical Eng. & Systems 2022-08-03 Shihui Yu , Chen Gong , Zhengyuan Xu

For spiking neural networks we consider the stability problem of global synchrony, arguably the simplest non-trivial collective dynamics in such networks. We find that even this simplest dynamical problem -- local stability of synchrony --…

Dynamical Systems · Mathematics 2009-11-13 Marc Timme , Fred Wolf

Given an undirected measurement graph $G = ([n], E)$, the classical angular synchronization problem consists of recovering unknown angles $\theta_1,\dots,\theta_n$ from a collection of noisy pairwise measurements of the form $(\theta_i -…

Machine Learning · Statistics 2021-01-06 Mihai Cucuringu , Hemant Tyagi

We study the problem of estimating the value of a known smooth function $f$ at an unknown point $\boldsymbol{\mu} \in \mathbb{R}^n$, where each component $\mu_i$ can be sampled via a noisy oracle. Sampling more frequently components of…

Machine Learning · Computer Science 2022-03-22 Tavor Z. Baharav , Gary Cheng , Mert Pilanci , David Tse

We present a general approach to the problem of determining the asymptotic order of the variance of the optimal score between two independent random sequences defined over an arbitrary finite alphabet. Our general approach is based on…

Probability · Mathematics 2012-11-22 Jüri Lember , Heinrich Matzinger , Felipe Torres

We consider the estimation of quadratic functionals in a Gaussian sequence model where the eigenvalues are supposed to be unknown and accessible through noisy observations only. Imposing smoothness assumptions both on the signal and the…

Statistics Theory · Mathematics 2019-07-16 Martin Kroll

Let $J(t)$ be the the integrated flux of particles in the symmetric simple exclusion process starting with the product invariant measure $\nu_\rho$ with density $\rho$. We compute its rescaled asymptotic variance: \[ \lim_{t\to\infty}…

Probability · Mathematics 2011-11-10 A. De Masi , P. A. Ferrari

As a complement to two recent papers by An and Yen [An, D.T.V., Yen, N.D.: Differential stability of convex optimization problems under inclusion constraints. Appl. Anal., 94, 108--128 (2015)], and by An and Yao [An, D.T.V., Yao, J.-C.:…

Optimization and Control · Mathematics 2018-05-07 Duong Thi Viet An , Jen-Chih Yao

We treat the statistical inference problems in which one needs to detect and estimate simultaneously using as small number of samples as possible. Conventional methods treat the detection and estimation subproblems separately, ignoring the…

Applications · Statistics 2014-11-07 Yasin Yilmaz , Shang Li , Xiaodong Wang

We study the volatility functional inference by Fourier transforms. This spectral framework is advantageous in that it harnesses the power of harmonic analysis to handle missing data and asynchronous observations without any artificial time…

Statistics Theory · Mathematics 2019-11-07 Richard Y. Chen

A high-order convergent and robust numerical solver is constructed and used to find complex eigenwavenumbers and electromagnetic eigenfields of dielectric objects with axial symmetry. The solver is based on Fourier--Nystr\"om discretization…

Computational Physics · Physics 2018-04-04 Johan Helsing , Anders Karlsson

Demixing is the problem of identifying multiple structured signals from a superimposed, undersampled, and noisy observation. This work analyzes a general framework, based on convex optimization, for solving demixing problems. When the…

Information Theory · Computer Science 2013-10-01 Michael B. McCoy , Joel A. Tropp

We consider an infinite horizon optimal control problem for a continuous-time Markov chain $X$ in a finite set $I$ with noise-free partial observation. The observation process is defined as $Y_t = h(X_t)$, $t \geq 0$, where $h$ is a given…

Optimization and Control · Mathematics 2018-06-04 Alessandro Calvia

In insertion-only streaming, one sees a sequence of indices $a_1, a_2, \ldots, a_m\in [n]$. The stream defines a sequence of $m$ frequency vectors $x^{(1)},\ldots,x^{(m)}\in\mathbb{R}^n$ with $(x^{(t)})_i = |\{j : j\in[t], a_j = i\}|$. That…

Data Structures and Algorithms · Computer Science 2017-11-10 Jarosław Błasiok , Jian Ding , Jelani Nelson

The stability of non-isolated equilibria to quasilinear parabolic problems of the form $u' = A(u)u + f(u)$ is established in interpolation spaces (and thus extending previous results relying on maximal regularity). The approach allows full…

Analysis of PDEs · Mathematics 2026-03-05 Bogdan-Vasile Matioc , Christoph Walker

Efficient solution of the lowest eigenmodes is studied for a family of related eigenvalue problems with common $2\times 2$ block structure. It is assumed that the upper diagonal block varies between different versions while the lower…

Numerical Analysis · Mathematics 2020-06-19 Antti Hannukainen , Jarmo Malinen , Antti Ojalammi

In this article we study a finite horizon optimal control problem with monotone controls. We consider the associated Hamilton-Jacobi-Bellman (HJB) equation which characterizes the value function. We consider the totally discretized problem…

Optimization and Control · Mathematics 2014-07-08 Eduardo A. Philipp , Laura S. Aragone , Lisandro A. Parente

Classical approximation and learning methods are typically optimized for interpolation over a sampled domain {\Omega}, with no guarantees on their behavior in an extrapolation region {\Xi}, where small in-domain errors may amplify. We…

Numerical Analysis · Mathematics 2026-03-11 Guy Hay , Nir Sharon

The notion of quasi-Fej\'er monotonicity has proven to be an efficient tool to simplify and unify the convergence analysis of various algorithms arising in applied nonlinear analysis. In this paper, we extend this notion in the context of…

Optimization and Control · Mathematics 2012-09-03 Patrick L. Combettes , Bang C. Vu