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Computing $p \rightarrow q$ norm for matrices is a classical problem in computational mathematics and power iteration is a well-known method for computing $p \rightarrow q $ norm for a matrix with nonnegative entries. Here we define an…

Numerical Analysis · Mathematics 2022-09-16 Mohammad ShahverdiKondori , Sio On Chan

In 2006 Carbery raised a question about an improvement on the na\"ive norm inequality $\|f+g\|_p^p \leq 2^{p-1}(\|f\|_p^p + \|g\|_p^p)$ for two functions in $L^p$ of any measure space. When $f=g$ this is an equality, but when the supports…

Functional Analysis · Mathematics 2018-12-11 Eric A. Carlen , Rupert L. Frank , Paata Ivanisvili , Elliott H. Lieb

In this paper, we bring forward a completely perturbed nonconvex Schatten $p$-minimization to address a model of completely perturbed low-rank matrix recovery. The paper that based on the restricted isometry property generalizes the…

Information Theory · Computer Science 2020-06-12 Jianwen Huang , Wendong Wang , Feng Zhang , Jianjun Wang

We give the first input-sparsity time algorithms for the rank-$k$ low rank approximation problem in every Schatten norm. Specifically, for a given $n\times n$ matrix $A$, our algorithm computes $Y,Z\in \mathbb{R}^{n\times k}$, which, with…

Data Structures and Algorithms · Computer Science 2020-07-01 Yi Li , David Woodruff

The Schatten-p quasi-norm $(0<p<1)$ is usually used to replace the standard nuclear norm in order to approximate the rank function more accurately. However, existing Schatten-p quasi-norm minimization algorithms involve singular value…

Numerical Analysis · Computer Science 2016-06-07 Fanhua Shang , Yuanyuan Liu , James Cheng

The main purpose of this paper is to englobe some new and known types of Hermitian block-matrices $M=\begin{pmatrix} A \& X\\ {X^*} \& B\end{pmatrix}$ satisfying or not the inequality $\|M\|\le \|A+B\|$ for all symmetric norms

Rings and Algebras · Mathematics 2018-07-10 Antoine Mhanna

We study the problem of efficient compression of a stochastic source of probability distributions. It can be viewed as a generalization of Shannon's source coding problem. It has relation to the theory of common randomness, as well as to…

Quantum Physics · Physics 2016-09-08 Andreas Winter

Let $\overline{p}(n)$ denote the overpartition funtion. This paper presents the $2$-$\log$-concavity property of $\overline{p}(n)$ by considering a more general inequality of the following form \begin{equation*} \begin{vmatrix}…

Number Theory · Mathematics 2022-01-21 Gargi Mukherjee

In the present paper, we provide several inequalities for the generalized numerical radius of operator matrices as introduced by A. Abu-omar and F. Kittaneh in [3]. We generalize the convexity and the log-convexity results obtained by M.…

Functional Analysis · Mathematics 2020-04-22 H. Abbas , S. Harb , H. Issa

We give sufficient conditions on a matrix A ensuring the existence of a partition of this matrix into two submatrices with extremely small norm of the image of any vector. Under some weak conditions on a matrix A we obtain a partition of A…

Functional Analysis · Mathematics 2020-09-24 Irina Limonova

This paper focuses on optimal constants and optimizers of the second order Caffarelli-Kohn-Nirenberg inequalities. Firstly, we aim to study optimal constants and optimizers for the following second order Caffarelli-Kohn-Nirenberg inequality…

Analysis of PDEs · Mathematics 2024-05-14 Xiao-Ping Chen , Chun-Lei Tang

We introduce a backward stable algorithm for computing the CS decomposition of a partitioned $2n \times n$ matrix with orthonormal columns, or a rank-deficient partial isometry. The algorithm computes two $n \times n$ polar decompositions…

Numerical Analysis · Mathematics 2018-04-25 Evan S. Gawlik , Yuji Nakatsukasa , Brian D. Sutton

Matrix concentration inequalities, intimately connected to the Non-Commutative Khintchine inequality, have been an important tool in both applied and pure mathematics. We study tensor versions of these inequalities, and establish…

Probability · Mathematics 2024-11-19 Afonso S. Bandeira , Sivakanth Gopi , Haotian Jiang , Kevin Lucca , Thomas Rothvoss

Recurrent neural networks can be large and compute-intensive, yet many applications that benefit from RNNs run on small devices with very limited compute and storage capabilities while still having run-time constraints. As a result, there…

Machine Learning · Computer Science 2020-08-14 Urmish Thakker , Jesse Beu , Dibakar Gope , Ganesh Dasika , Matthew Mattina

Fitting a matrix of a given rank to data in a least squares sense can be done very effectively using 2nd order methods such as Levenberg-Marquardt by explicitly optimizing over a bilinear parameterization of the matrix. In contrast, when…

Computer Vision and Pattern Recognition · Computer Science 2020-07-10 José Pedro Iglesias , Carl Olsson , Marcus Valtonen Örnhag

For every $p\leq n$ positive integer we obtain the lower bound $(3-\frac{1}{p+1})n^2-\big(2\binom{2p}{p+1}-\binom{2p-2}{p-1}+2\big)n$ for the rank of the $n\times n$ matrix multiplication. This bound improves the previous one…

Computational Complexity · Computer Science 2013-11-08 Alex Massarenti , Emanuele Raviolo

The distillability conjecture of two-copy 4 by 4 Werner states is one of the main open problems in quantum information. We prove two special cases of the conjecture. The first case occurs when two 4 by 4 matrices A, B are both unitarily…

Quantum Physics · Physics 2024-11-15 Saiqi Liu , Chen Lin

Let N and M be von Neumann algebras. It is proved that L^p(N) does not Banach embed in L^p(M) for N infinite, M finite, 1 < or = p < 2. The following considerably stronger result is obtained (which implies this, since the Schatten p-class…

Functional Analysis · Mathematics 2007-05-23 U. Haagerup , H. P. Rosenthal , F. A. Sukochev

A generalization of the Bernstein matrix concentration inequality to random tensors of general order is proposed. This generalization is based on the use of Einstein products between tensors, from which a strong link can be established…

Statistics Theory · Mathematics 2021-05-31 Z. Luo , L. Qi , Ph. L. Toint

We analyze the global convergence of the power iterates for the computation of a general mixed-subordinate matrix norm. We prove a new global convergence theorem for a class of entrywise nonnegative matrices that generalizes and improves a…

Numerical Analysis · Mathematics 2020-02-07 Antoine Gautier , Matthias Hein , Francesco Tudisco