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Related papers: Concentration inequalities for random tensors

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We analyze low rank tensor completion (TC) using noisy measurements of a subset of the tensor. Assuming a rank-$r$, order-$d$, $N \times N \times \cdots \times N$ tensor where $r=O(1)$, the best sampling complexity that was achieved is…

Machine Learning · Computer Science 2017-11-15 Navid Ghadermarzy , Yaniv Plan , Özgür Yılmaz

Let $(X_i)_{i=1,...,n}$ be a possibly nonstationary sequence such that $\mathscr{L}(X_i)=P_n$ if $i\leq n\theta$ and $\mathscr{L}(X_i)=Q_n$ if $i>n\theta$, where $0<\theta <1$ is the location of the change-point to be estimated. We…

Statistics Theory · Mathematics 2009-09-29 Samir Ben Hariz , Jonathan J. Wylie , Qiang Zhang

This paper addresses the detection of a low rank high-dimensional tensor corrupted by an additive complex Gaussian noise. In the asymptotic regime where all the dimensions of the tensor converge towards $+\infty$ at the same rate, existing…

Signal Processing · Electrical Eng. & Systems 2018-02-21 Antoine Chevreuil , Philippe Loubaton

We study the problem of testing whether two tensors in $\mathbb{R}^\ell\otimes \mathbb{R}^m\otimes \mathbb{R}^n$ are isomorphic under the natural action of orthogonal groups $\textbf{O}(\ell, \mathbb{R})\times\textbf{O}(m,…

Computational Complexity · Computer Science 2026-03-31 Jeremy Chizewer , Samuel Everett , Deven Mithal , Youming Qiao

We investigate the in-context learning capabilities of transformers for the $d$-dimensional mixture of linear regression model, providing theoretical insights into their existence, generalization bounds, and training dynamics. Specifically,…

Machine Learning · Statistics 2025-02-11 Yanhao Jin , Krishnakumar Balasubramanian , Lifeng Lai

We prove two basic conjectures on the distribution of the smallest singular value of random n times n matrices with independent entries. Under minimal moment assumptions, we show that the smallest singular value is of order n^{-1/2}, which…

Probability · Mathematics 2016-12-23 Mark Rudelson , Roman Vershynin

We consider a pair of causally independent processes, modelled as the tensor product of two channels, acting on a possibly correlated input to produce random outputs X and Y. We show that, assuming the processes produce a sufficient amount…

Quantum Physics · Physics 2025-10-08 Martin Sandfuchs , Carla Ferradini , Renato Renner

Let $f_1,\dots,f_k \in \mathbb{R}[X]$ be polynomials of degree at most $d$ with $f_1(0)=\dots=f_k(0)=0$. We show that there is an $n<x$ such that $\|f_i(n)\|\ll x^{-1/10.5kd(d-1)+o(1)}$ for all $1\le i\le k$. This improves on an earlier…

Number Theory · Mathematics 2024-07-03 Cheuk Fung Lau

The classical Erd\H{o}s-Littlewood-Offord problem concerns the random variable $X = a_1 \xi_1 + \dots + a_n \xi_n$, where $a_i \in \mathbb{R} \setminus \{0\}$ are fixed and $\xi_i \sim \text{Ber}(1/2)$ are independent. The…

Combinatorics · Mathematics 2020-01-03 Mihir Singhal

We investigate the uniqueness of decomposition of general tensors $T\in {\mathbb C}^{n_1+1}\otimes\cdots\otimes{\mathbb C}^{n_r+1}$ as a sum of tensors of rank $1$. This is done extending the theory developed in a previous paper by the…

Algebraic Geometry · Mathematics 2020-09-03 Alex Casarotti , Massimiliano Mella

Let A_n=(a_{ij})_{i,j=1}^n be an n\times n positive matrix with entries in [a,b], 0<a\le b. Let X_n=(\sqrta_{ij}x_{ij})_{i,j=1}^n be a random matrix, where {x_{ij}} are i.i.d. N(0,1) random variables. We show that for large n, \det…

Probability · Mathematics 2007-05-23 Shmuel Friedland , Brian Rider , Ofer Zeitouni

We give necessary and sufficient conditions for two sub-vectors of a random vector with a multivariate extreme value distribution, corresponding to the limit distribution of the maximum of a multidimensional stationary sequence with…

Probability · Mathematics 2010-06-09 Clara Viseu , Luísa Pereira , Ana Paula Martins , Helena Ferreira

We derive concentration inequalities for the spectral measure of large random matrices, allowing for certain forms of dependence. Our main focus is on empirical covariance (Wishart) matrices, but general symmetric random matrices are also…

Statistics Theory · Mathematics 2018-09-24 Adityanand Guntuboyina , Hannes Leeb

In this paper we discuss the notion of singular vector tuples of a complex valued $d$-mode tensor of dimension m_1 x ... x m_d. We show that a generic tensor has a finite number of singular vector tuples, viewed as points in the…

Algebraic Geometry · Mathematics 2013-11-11 Shmuel Friedland , Giorgio Ottaviani

We prove the following statement. Let $f\in\mathbb{R}[x_1,\ldots,x_d]$, for some $d\ge 3$, and assume that $f$ depends non-trivially in each of $x_1,\ldots,x_d$. Then one of the following holds. (i) For every finite sets…

Combinatorics · Mathematics 2018-07-09 Orit E. Raz , Zvi Shem Tov

In statistics, assuming samples are independent is reasonable. However, this property can fail to hold for the features, a distinction that has led to several lines of work aiming to remove the latter assumption of independence present in…

Probability · Mathematics 2026-02-03 Simona Diaconu

We introduce a new generalization of relative entropy to non-negative vectors with sums $\gt 1$. We show in a purely combinatorial setting, with no probabilistic considerations, that in the presence of linear constraints defining a convex…

Information Theory · Computer Science 2024-05-08 Kostas N. Oikonomou

Restriction is a natural quasi-order on $d$-way tensors. We establish a remarkable aspect of this quasi-order in the case of tensors over a fixed finite field -- namely, that it is a well-quasi-order: it admits no infinite antichains and no…

Algebraic Geometry · Mathematics 2025-09-03 Andreas Blatter , Jan Draisma , Filip Rupniewski

The largest eigenvalue of random tensors is an important feature of systems involving disorder, equivalent to the ground state energy of glassy systems or to the injective norm of quantum states. For symmetric Gaussian random tensors of…

High Energy Physics - Theory · Physics 2024-12-16 Nicolas Delporte , Naoki Sasakura

The martingale method is used to establish concentration inequalities for a class of dependent random sequences on a countable state space, with the constants in the inequalities expressed in terms of certain mixing coefficients. Along the…

Probability · Mathematics 2009-01-22 Leonid , Kontorovich , Kavita Ramanan
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