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We consider a \emph{code} to be a subset of the vertex set of a \emph{Hamming graph}. In this setting a \emph{neighbour} of the code is a vertex which differs in exactly one entry from some codeword. This paper examines codes with the…

Combinatorics · Mathematics 2014-04-08 Neil I. Gillespie , Cheryl E. Praeger

We explain how to optimize finite-length LDPC codes for transmission over the binary erasure channel. Our approach relies on an analytic approximation of the erasure probability. This is in turn based on a finite-length scaling result to…

Information Theory · Computer Science 2007-07-13 Abdelaziz Amraoui , Andrea Montanari , Ruediger Urbanke

Recently, one has seen a surge of interest in developing such methods including ones for learning such representations for (undirected) graphs (while preserving important properties). However, most of the work to date on embedding graphs…

Social and Information Networks · Computer Science 2018-11-30 Jiankai Sun , Srinivasan Parthasarathy

The framework of feedback graphs is a generalization of sequential decision-making with bandit or full information feedback. In this work, we study an extension where the directed feedback graph is stochastic, following a distribution…

Machine Learning · Computer Science 2024-02-20 Emmanuel Esposito , Federico Fusco , Dirk van der Hoeven , Nicolò Cesa-Bianchi

Distributed storage systems that deploy erasure codes can provide better features such as lower storage overhead and higher data reliability. In this paper, we focus on fractional repetition (FR) codes, which are a class of storage codes…

Information Theory · Computer Science 2020-05-15 Bing Zhu , Kenneth W. Shum , Hui Li

A storage code is an assignment of symbols to the vertices of a connected graph $G(V,E)$ with the property that the value of each vertex is a function of the values of its neighbors, or more generally, of a certain neighborhood of the…

Information Theory · Computer Science 2023-08-29 Alexander Barg , Ohad Elishco , Ryan Gabrys , Geyang Wang , Eitan Yaakobi

Node embedding is the task of extracting informative and descriptive features over the nodes of a graph. The importance of node embeddings for graph analytics, as well as learning tasks such as node classification, link prediction and…

Machine Learning · Computer Science 2019-06-17 Dimitris Berberidis , Georgios B. Giannakis

Determining how the brain stores information is one of the most pressing problems in neuroscience. In many instances, the collection of stimuli for a given neuron can be modeled by a convex set in $\mathbb{R}^d$. Combinatorial objects known…

Combinatorics · Mathematics 2019-05-29 R. Amzi Jeffs , Mohamed Omar , Natchanon Suaysom , Aleina Wachtel , Nora Youngs

We address the problem of reasoning on graph transformations featuring actions such as \emph{addition} and \emph{deletion} of nodes and edges, node \emph{merging} and \emph{cloning}, node or edge \emph{labelling} and edge…

Logic in Computer Science · Computer Science 2018-03-08 Jon Haël Brenas , Rachid Echahed , Martin Strecker

We present the construction of a family of erasure correcting codes for distributed storage that achieve low repair bandwidth and complexity at the expense of a lower fault tolerance. The construction is based on two classes of codes, where…

Information Theory · Computer Science 2018-09-03 Siddhartha Kumar , Alexandre Graell i Amat , Iryna Andriyanova , Fredrik Brännström , Eirik Rosnes

Link and node failures are two common fundamental problems that affect operational networks. Protection of communication networks against such failures is essential for maintaining network reliability and performance. Network protection…

Information Theory · Computer Science 2010-08-26 Salah A. Aly , Ahmed E. Kamal , Anwar I. Walid

The guessing number of a directed graph (digraph), equivalent to the entropy of that digraph, was introduced as a direct criterion on the solvability of a network coding instance. This paper makes two contributions on the guessing number.…

Information Theory · Computer Science 2015-03-17 Maximilien Gadouleau , Soren Riis

MDS array codes are widely used in storage systems due to their computationally efficient encoding and decoding procedures. An MDS code with $r$ redundancy nodes can correct any $r$ node erasures by accessing all the remaining information…

Information Theory · Computer Science 2016-03-04 Zhiying Wang , Itzhak Tamo , Jehoshua Bruck

Error-correcting codes over sets, with applications to DNA storage, are studied. The DNA-storage channel receives a set of sequences, and produces a corrupted version of the set, including sequence loss, symbol substitution, symbol…

Information Theory · Computer Science 2021-07-12 Hengjia Wei , Moshe Schwartz

Just as semantic hashing can accelerate information retrieval, binary valued embeddings can significantly reduce latency in the retrieval of graphical data. We introduce a simple but effective model for learning such binary vectors for…

Machine Learning · Computer Science 2018-03-28 Vinith Misra , Sumit Bhatia

An identifying code of a graph is a subset of its vertices such that every vertex of the graph is uniquely identified by the set of its neighbours within the code. We study the edge-identifying code problem, i.e. the identifying code…

Combinatorics · Mathematics 2014-03-19 Florent Foucaud , Sylvain Gravier , Reza Naserasr , Aline Parreau , Petru Valicov

We present a one-shot method for compressing large labeled graphs called Random Edge Coding. When paired with a parameter-free model based on P\'olya's Urn, the worst-case computational and memory complexities scale quasi-linearly and…

Machine Learning · Computer Science 2023-05-18 Daniel Severo , James Townsend , Ashish Khisti , Alireza Makhzani

Maximum distance separable (MDS) codes are optimal error-correcting codes in the sense that they provide the maximum failure-tolerance for a given number of parity nodes. Suppose that an MDS code with $k$ information nodes and $r=n-k$…

Information Theory · Computer Science 2016-04-11 Min Ye , Alexander Barg

We propose a novel node embedding of directed graphs to statistical manifolds, which is based on a global minimization of pairwise relative entropy and graph geodesics in a non-linear way. Each node is encoded with a probability density…

Machine Learning · Computer Science 2020-02-07 Thorben Funke , Tian Guo , Alen Lancic , Nino Antulov-Fantulin

The state of the art in Grid style data management is to achieve increased resilience of data via multiple complete replicas of data files across multiple storage endpoints. While this is effective, it is not the most space-efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-01-20 Samuel Cadellin Skipsey , Paulin Todev , David Britton , David Crooks , Gareth Roy