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Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina

Let $A_n=(a_0,a_1,\dots,a_{n-1})$ be drawn uniformly at random from $\{-1,+1\}^n$ and define \[ M(A_n)=\max_{0<u<n}\,\Bigg|\sum_{j=0}^{n-u-1}a_ja_{j+u}\Bigg|\quad\text{for $n>1$}. \] It is proved that $M(A_n)/\sqrt{n\log n}$ converges in…

Combinatorics · Mathematics 2014-03-18 Kai-Uwe Schmidt

Let $F_n$ be an $n$ by $n$ symmetric matrix whose entries are bounded by $n^{\gamma}$ for some $\gamma>0$. Consider a randomly perturbed matrix $M_n=F_n+X_n$, where $X_n$ is a random symmetric matrix whose upper diagonal entries $x_{ij}$…

Combinatorics · Mathematics 2011-03-18 Hoi H. Nguyen

In this paper, we study the restricted isometry property of partial random circulant matrices. For a bounded subgaussian generator with independent entries, we prove that the partial random circulant matrices satisfy $s$-order RIP with high…

Information Theory · Computer Science 2018-08-23 Meng Huang , Yuxuan Pang , Zhiqiang Xu

Trace reconstruction is the problem of learning an unknown string $x$ from independent traces of $x$, where traces are generated by independently deleting each bit of $x$ with some deletion probability $q$. In this paper, we initiate the…

Data Structures and Algorithms · Computer Science 2020-12-15 Shyam Narayanan , Michael Ren

Permanents of random matrices with independent and identically distributed (i.i.d.) entries have extensively studied in literature and convergence and concentration properties are known under varying assumptions on the distributions. In…

Probability · Mathematics 2021-12-13 Ghurumuruhan Ganesan

A novel matrix approximation problem is considered herein: observations based on a few fully sampled columns and quasi-polynomial structural side information are exploited. The framework is motivated by quantum chemistry problems wherein…

Signal Processing · Electrical Eng. & Systems 2023-05-23 Jeongmin Chae , Praneeth Narayanamurthy , Selin Bac , Shaama Mallikarjun Sharada , Urbashi Mitra

In this paper, we study the following problem of reconstructing a simple polygon: Given a cyclically ordered vertex sequence of an unknown simple polygon P of n vertices and, for each vertex v of P, the sequence of angles defined by all the…

Computational Geometry · Computer Science 2010-09-15 Danny Z. Chen , Haitao Wang

An unknown vector f in R^n can be recovered from corrupted measurements y = Af + e where A^(m*n)(m>n) is the coding matrix if the unknown error vector e is sparse. We investigate the relationship of the fraction of errors and the recovering…

Information Theory · Computer Science 2010-06-03 Meng Wang , Weiyu Xu , Ao Tang

Computation of the probability that a random graph is connected is a challenging problem, so it is natural to turn to approximations such as Monte Carlo methods. We describe sequential importance resampling and splitting algorithms for the…

Computation · Statistics 2015-06-04 Rohan Shah , Dirk P. Kroese

An arbitrary $m\times n$ Boolean matrix $M$ can be decomposed {\em exactly} as $M =U\circ V$, where $U$ (resp. $V$) is an $m\times k$ (resp. $k\times n$) Boolean matrix and $\circ$ denotes the Boolean matrix multiplication operator. We…

Discrete Mathematics · Computer Science 2015-12-29 Yuan Sun , Shiwei Ye , Yi Sun , Tsunehiko Kameda

An $(m,n,a,b)$-tensor code consists of $m\times n$ matrices whose columns satisfy `$a$' parity checks and rows satisfy `$b$' parity checks (i.e., a tensor code is the tensor product of a column code and row code). Tensor codes are useful in…

Information Theory · Computer Science 2022-12-05 Joshua Brakensiek , Sivakanth Gopi , Visu Makam

We revisit the asymptotic analysis of probabilistic construction of adjacency matrices of expander graphs proposed in [4]. With better bounds we derived a new reduced sample complexity for the number of nonzeros per column of these…

Information Theory · Computer Science 2018-05-17 Bubacarr Bah , Jared Tanner

The insertion-deletion channel takes as input a bit string ${\bf x}\in\{0,1\}^{n}$, and outputs a string where bits have been deleted and inserted independently at random. The trace reconstruction problem is to recover $\bf x$ from many…

Probability · Mathematics 2020-04-28 Nina Holden , Robin Pemantle , Yuval Peres , Alex Zhai

The Harary reconstruction conjecture states that any graph with more than four edges can be uniquely reconstructed from its set of maximal edge-deleted subgraphs. In 1977, M\"uller verified the conjecture for graphs with $n$ vertices and $n…

Combinatorics · Mathematics 2024-11-06 Anthony E. Pizzimenti , Umarkhon Rakhimov

Why does the low dimensionality of representations, typically $d\approx 1000$, not prevent modern embedding-based retrieval models from scaling to billions, or even trillions, of data points? To answer this question, we study maximal-margin…

Machine Learning · Computer Science 2026-05-25 Kiril Bangachev , Guy Bresler , Jonathan Kogan , Yury Polyanskiy

How to construct a suitable measurement matrix is still an open question in compressed sensing. A significant part of the recent work is that the measurement matrices are not completely random on the entries but exhibit considerable…

Information Theory · Computer Science 2017-09-08 Tao Huang , Yi-Zheng Fan , Ming Zhu

Graph reconstruction can efficiently detect the underlying topology of massive networks such as the Internet. Given a query oracle and a set of nodes, the goal is to obtain the edge set by performing as few queries as possible. An algorithm…

Data Structures and Algorithms · Computer Science 2024-07-29 Clara Stegehuis , Lotte Weedage

We present a randomized approximation scheme for the permanent of a matrix with nonnegative entries. Our scheme extends a recursive rejection sampling method of Huber and Law (SODA 2008) by replacing the upper bound for the permanent with a…

Data Structures and Algorithms · Computer Science 2021-08-18 Juha Harviainen , Antti Röyskö , Mikko Koivisto

One tuple of probability vectors is more informative than another tuple when there exists a single stochastic matrix transforming the probability vectors of the first tuple into the probability vectors of the other. This is called matrix…

Statistics Theory · Mathematics 2024-04-26 Muhammad Usman Farooq , Tobias Fritz , Erkka Haapasalo , Marco Tomamichel