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In the negative perceptron problem we are given $n$ data points $({\boldsymbol x}_i,y_i)$, where ${\boldsymbol x}_i$ is a $d$-dimensional vector and $y_i\in\{+1,-1\}$ is a binary label. The data are not linearly separable and hence we…

Machine Learning · Computer Science 2025-03-25 Andrea Montanari , Yiqiao Zhong , Kangjie Zhou

We consider a stochastic process in which independent identically distributed random matrices are multiplied and where the Lyapunov exponent of the product is positive. We continue multiplying the random matrices as long as the norm,…

Statistical Mechanics · Physics 2018-03-14 Michael Wilkinson , John Grant

We observe the Galton-Watson Branching Processes. Limit properties of transition functions and their convergence to invariant measures are investigated.

Probability · Mathematics 2019-04-23 Azam A. Imomov , Erkin E. Tukhtaev

Consider a $n\times n$ sparse non-Hermitian random matrix $X_n$ defined as the Hadamard product between a random matrix with centered independent and identically distributed entries and a sparse Bernoulli matrix with success probability…

Probability · Mathematics 2026-02-25 Walid Hachem , Michail Louvaris , Jamal Najim

In this paper we consider a triangular array of branching processes with non-stationary immigration. We prove a weak convergence of properly normalized branching processes with immigration to deterministic function under assumption that…

Probability · Mathematics 2022-04-25 Sadillo Sharipov

We study a continuous time branching process where an individual splits into two daughters with rate b and dies with rate a, starting from a single individual at t=0. We show that the model can be mapped exactly to a random walk problem…

Statistical Mechanics · Physics 2026-02-13 Satya N. Majumdar , Alberto Rosso

We study the largest eigenvalue of a Gaussian random symmetric matrix $X_n$, with zero-mean, unit variance entries satisfying the condition $\sup_{(i, j) \ne (i', j')}|\mathbb{E}[X_{ij} X_{i'j'}]| = O(n^{-(1 + \varepsilon)})$, where…

Probability · Mathematics 2025-02-10 Debapratim Banerjee , Soumendu Sundar Mukherjee , Dipranjan Pal

We establish large deviation principle (LDP) for the family of vector-valued random processes $(X^\epsilon,Y^\epsilon),\epsilon\to 0$ defined as $$ X^\epsilon_t=\frac{1}{\epsilon^\kappa}\int_0^t H(\xi^\epsilon_s,Y^\epsilon_s)ds,…

Probability · Mathematics 2016-09-07 A. Guillin , R. Liptser

We prove a general fluctuation limit theorem for Galton-Watson branching processes with immigration. The limit is a time-inhomogeneous OU type process driven by a spectrally positive Levy process. As applications of this result, we obtain…

Probability · Mathematics 2009-09-12 Chunhua Ma

This work provides a brief introduction to continuous-state branching processes (CB-processes) and continuous-state branching processes with immigration (CBI-processes) accessible to graduate students with reasonable background in…

Probability · Mathematics 2019-01-14 Zenghu Li

We consider a $\mathbb{R}^d$-valued branching random walk with a stationary and ergodic environment $\xi=(\xi_n)$ indexed by time $n\in\mathbb{N}$. Let $Z_n$ be the counting measure of particles of generation $n$. With the help of the…

Probability · Mathematics 2019-10-15 Chunmao Huang , Xin Wang , Xiaoqiang Wang

Let $(\xi_i,\mathcal{F}_i)_{i\geq1}$ be a sequence of martingale differences. Set $S_n=\sum_{i=1}^n\xi_i $ and $[ S]_n=\sum_{i=1}^n \xi_i^2.$ We prove a Cram\'er type moderate deviation expansion for $\mathbf{P}(S_n/\sqrt{[ S]_n} \geq x)$…

Probability · Mathematics 2020-05-11 Xiequan Fan , Ion Grama , Quansheng Liu , Qi-Man Shao

We give the distribution function of $M_n$, the maximum of a sequence of $n$ observations from an autoregressive process of order 2. Solutions are first given in terms of repeated integrals and then for the case, where the underlying random…

Statistics Theory · Mathematics 2010-02-02 C. S. Withers , S. Nadarajah

In this article, we study the extremal processes of branching Brownian motions conditioned on having an unusually large maximum. The limiting point measures form a one-parameter family and are the decoration point measures in the extremal…

Probability · Mathematics 2020-09-01 Julien Berestycki , Éric Brunet , Aser Cortines , Bastien Mallein

In this article we consider Wigner matrices $X_N$ with variance profiles (also called Wigner-type matrices) which are of the form $X_N(i,j) = \sigma(i/N,j/N) a_{i,j} / \sqrt{N}$ where $\sigma$ is a symmetric real positive function of…

Probability · Mathematics 2023-03-01 Jonathan Husson

We develop a martingale approximation framework yielding quantitative maximal large deviations estimates for invertible dynamical systems. From suitable decay of correlations, we deduce these estimates and, as an application, we obtain…

Dynamical Systems · Mathematics 2026-05-08 José F. Alves , João S. Matias , Ian Melbourne

For a continuous-time Bienaym\'e-Galton-Watson process, $X$, with immigration and culling, $0$ as an absorbing state, call $X^q$ the process that results from killing $X$ at rate $q\in (0,\infty)$, followed by stopping it on extinction or…

Probability · Mathematics 2021-07-23 Matija Vidmar

Let $(Z_n)$ be a supercritical branching process with immigration in a random environment. The small positive values and some lower deviation inequalities for $Z$ are investigated. Based on these results, the central limit theorem of $\log…

Probability · Mathematics 2024-06-28 Yinxuan Zhao , Mei Zhang

The current paper focuses on studying the impact of immigration with an infinite mean, driven by a discrete-stable compound Poisson process, when it is entering the branching environment with infinite variance of reproduction. Our goal is…

Probability · Mathematics 2025-04-01 Maroussia Slavtchova-Bojkova , Penka Mayster

It has been proved by Bovier & Hartung [Elect. J. Probab. 19 (2014)] that the maximum of a variable-speed branching Brownian motion (BBM) in the weak correlation regime converges to a randomly shifted Gumbel distribution. The random shift…

Probability · Mathematics 2017-12-13 Constantin Glenz , Nicola Kistler , Marius A. Schmidt