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Assume that we observe a sample of size n composed of p-dimensional signals, each signal having independent entries drawn from a scaled Poisson distribution with an unknown intensity. We are interested in estimating the sum of the n unknown…

Statistics Theory · Mathematics 2018-01-19 Olivier Collier , Arnak Dalalyan

Under natural assumptions, an unstable equilibrium of a difference equation can be stabilized by a bounded multiplicative noise, identically distributed at each step. This includes stabilization of an otherwise unstable positive equilibrium…

Dynamical Systems · Mathematics 2022-08-22 Elena Braverman , Alexandra Rodkina

Unevenly spaced samples from a periodic function are common in signal processing and can often be viewed as a perturbed equally spaced grid. In this paper, we analyze how the uneven distribution of the samples impacts the quality of…

Numerical Analysis · Mathematics 2023-04-11 Annan Yu , Alex Townsend

Let $p_n(y)=\sum_k\hat{\alpha}_k\phi(y-k)+\sum_{l=0}^{j_n-1}\sum_k\hat {\beta}_{lk}2^{l/2}\psi(2^ly-k)$ be the linear wavelet density estimator, where $\phi$, $\psi$ are a father and a mother wavelet (with compact support),…

Statistics Theory · Mathematics 2009-08-31 Evarist Giné , Richard Nickl

Majority dynamics on a graph $G$ is a deterministic process such that every vertex updates its $\pm 1$-assignment according to the majority assignment on its neighbor simultaneously at each step. Benjamini, Chan, O'Donnel, Tamuz and Tan…

Combinatorics · Mathematics 2024-02-09 Debsoumya Chakraborti , Jeong Han Kim , Joonkyung Lee , Tuan Tran

Mitigating the negative impact of noisy labels has been aperennial issue in supervised learning. Robust loss functions have emerged as a prevalent solution to this problem. In this work, we introduce the Variation Ratio as a novel property…

Machine Learning · Computer Science 2025-11-18 Jialiang Wang , Xiong Zhou , Xianming Liu , Gangfeng Hu , Deming Zhai , Junjun Jiang , Haoliang Li

We consider the Cahn-Hilliard equation in one space dimension, perturbed by the derivative of a space and time white noise of intensity $\epsilon^{\frac 12}$, and we investigate the effect of the noise, as $\epsilon \to 0$, on the solutions…

Mathematical Physics · Physics 2022-12-22 L. Bertini , S. Brassesco , P. Buttà

The noise can stabilize a fluctuating or a periodically driven metastable state in such a way that the system remains in this state for a longer time than in the absence of white noise. This is the noise enhanced stability phenomenon,…

Statistical Mechanics · Physics 2007-05-23 Bernardo Spagnolo , Nikolay V. Agudov , Alexander A. Dubkov

On the basis of the competing cubic-quintic nonlinearity model, stability (instability) of continuous waves in nonlocal random non-Kerr nonlinear media is studied analytically and numerically. Fluctuating media parameters are modeled by the…

Pattern Formation and Solitons · Physics 2008-04-24 Maxim A. Molchan

This paper studies finite-sample set-membership identification for discrete-time bilinear systems under bounded symmetric log-concave disturbances. Compared with existing finite-sample results for linear systems and related analyses under…

Machine Learning · Computer Science 2026-03-24 Hongyu Yi , Chenbei Lu , Jing Yu

Assign independent weights to the edges of the square lattice, from the uniform distribution on $\{a,b\}$ for some $0<a<b<\infty$. The weighted graph induces a random metric on $\mathbb{Z}^2$. Let $T_n$ denote the distance between $(0,0)$…

Probability · Mathematics 2025-06-25 Daniel Ahlberg , Daniel de la Riva

An unbiased estimator for the ellipticity of an object in a noisy image is given in terms of the image moments. Three assumptions are made: i) the pixel noise is normally distributed, although with arbitrary covariance matrix, ii) the image…

Cosmology and Nongalactic Astrophysics · Physics 2017-08-09 Nicolas Tessore

We study how much noise can be tolerated by a universal gate set before it loses its quantum-computational power. Specifically we look at circuits with perfect stabilizer operations in addition to imperfect non-stabilizer gates. We prove…

Quantum Physics · Physics 2009-12-24 Wim van Dam , Mark Howard

A quantum computer -- i.e., a computer capable of manipulating data in quantum superposition -- would find applications including factoring, quantum simulation and tests of basic quantum theory. Since quantum superpositions are fragile, the…

Quantum Physics · Physics 2007-05-23 Ben W. Reichardt

This paper studies problems of inferring order given noisy information. In these problems there is an unknown order (permutation) $\pi$ on $n$ elements denoted by $1,...,n$. We assume that information is generated in a way correlated with…

Data Structures and Algorithms · Computer Science 2009-10-08 Mark Braverman , Elchanan Mossel

In recent years, the mathematical limits and algorithmic bounds for probabilistic group testing have become increasingly well-understood, with exact asymptotic thresholds now being known in general scaling regimes for the noiseless setting.…

Information Theory · Computer Science 2024-10-24 Junren Chen , Jonathan Scarlett

The data $(y_i,x_i)\in$ $\textbf{R}\times[a,b]$, $i=1,\ldots,n$ satisfy $y_i=s(x_i)+e_i$ where $s$ belongs to the set of cubic splines. The unknown noises $(e_i)$ are such that $var(e_I)=1$ for some $I\in \{1, \ldots, n\}$ and…

Statistics Theory · Mathematics 2014-06-09 Azzouz Dermoune , Aziz El Kaabouchi

This paper proposes normative criteria for voting rules under uncertainty about individual preferences. The criteria emphasize the importance of responsiveness, i.e., the probability that the social outcome coincides with the realized…

Theoretical Economics · Economics 2025-07-31 Satoshi Nakada , Shmuel Nitzan , Takashi Ui

We extend results by Stotland and Di Ventra on the phenomenon of resistive switching aided by noise. We further the analysis of the mechanism underlying the beneficial role of noise and study the EPIR (Electrical Pulse Induced Resistance)…

Mesoscale and Nanoscale Physics · Physics 2014-05-30 G. A. Patterson , P. I. Fierens , D. F. Grosz

We prove the hardness of weakly learning halfspaces in the presence of adversarial noise using polynomial threshold functions (PTFs). In particular, we prove that for any constants $d \in \mathbb{Z}^+$ and $\varepsilon > 0$, it is NP-hard…

Computational Complexity · Computer Science 2017-07-07 Arnab Bhattacharyya , Suprovat Ghoshal , Rishi Saket