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In this work we develop a theory of hierarchical clustering for graphs. Our modeling assumption is that graphs are sampled from a graphon, which is a powerful and general model for generating graphs and analyzing large networks. Graphons…

Machine Learning · Statistics 2017-05-24 Justin Eldridge , Mikhail Belkin , Yusu Wang

The paper proposes a theoretical approach of the debugging of constraint programs based on a notion of explanation tree. The proposed approach is an attempt to adapt algorithmic debugging to constraint programming. In this theoretical…

Software Engineering · Computer Science 2007-05-23 Gerard Ferrand , Willy Lesaint , Alexandre Tessier

We introduce \emph{Term Coding}, a novel framework for analysing extremal problems in discrete mathematics by encoding them as finite systems of \emph{term equations} (and, optionally, \emph{non-equality constraints}). In its basic form,…

Combinatorics · Mathematics 2025-10-07 Søren Riis

While feasibility and obtaining a solution of a given network coding problem are well studied, the decoding procedure and complexity have not garnered much attention. We consider the decoding problem in a network wherein the sources…

Information Theory · Computer Science 2015-10-14 Anindya Gupta , B. Sundar Rajan

Permutation codes are a class of structured vector quantizers with a computationally-simple encoding procedure based on sorting the scalar components. Using a codebook comprising several permutation codes as subcodes preserves the…

Information Theory · Computer Science 2015-03-13 Ha Q. Nguyen , Lav R. Varshney , Vivek K Goyal

Geometric modeling by constraints leads to large systems of algebraic equations. This paper studies bipartite graphs underlaid by systems of equations. It shows how these graphs make possible to polynomially decompose these systems into…

Discrete Mathematics · Computer Science 2014-05-26 Samy Ait-Aoudia , Roland Jegou , Dominique Michelucci

Cyclic codes over finite fields are widely implemented in data storage systems, communication systems, and consumer electronics, as they have very efficient encoding and decoding algorithms. They are also important in theory, as they are…

Information Theory · Computer Science 2024-12-03 Cunsheng Ding

Specify a randomized algorithm that, given a very large graph or network, extracts a random subgraph. What can we learn about the input graph from a single subsample? We derive laws of large numbers for the sampler output, by relating…

Statistics Theory · Mathematics 2017-10-13 Peter Orbanz

In this paper we extend the relation between convolutional codes and linear systems over finite fields to certain commutative rings through first order representations . We introduce the definition of rings with representations as those for…

Optimization and Control · Mathematics 2016-09-19 Miguel V. Carriegos , Noemí DeCastro-García , Ángel Luis Muñoz Castañeda

In extreme classification problems, learning algorithms are required to map instances to labels from an extremely large label set. We build on a recent extreme classification framework with logarithmic time and space, and on a general…

Machine Learning · Computer Science 2018-12-13 Itay Evron , Edward Moroshko , Koby Crammer

We demonstrate that certain Johnson-type bounds are asymptotically exact for a variety of classes of codes, namely, constant-composition codes, nonbinary constant-weight codes and multiply constant-weight codes. This was achieved via an…

Combinatorics · Mathematics 2014-01-21 Yeow Meng Chee , Fei Gao , Han Mao Kiah , Alan Chi Hung Ling , Hui Zhang , Xiande Zhang

Spread codes and orbit codes are special families of constant dimension subspace codes. These codes have been well-studied for their error correction capability and transmission rate, but the question of how to encode messages has not been…

Information Theory · Computer Science 2014-09-03 Anna-Lena Trautmann

We present a structure associated to the class of linear codes. The properties of that structure are similar to some structures in the linear algebra techniques into the framework of the Gr\"obner bases tools. It allows to get some insight…

Commutative Algebra · Mathematics 2007-05-23 M. Borges-Quintana , M. Borges-Trenard , E. Martinez-Moro

We introduce a theory for encoding and manipulating algebraic data on categories via $\textit{concentration structures}$, which are equivalence relations on morphisms that satisfy certain axioms. For any category with a concentration…

Category Theory · Mathematics 2025-10-10 Yangxiao Luo , Shunyu Wan

Code clone detection is involved with detecting duplicated fragments of code within a code base. Detecting these clones is useful for maintenance operations which require editing the clones. The tools developed are expected to be robust…

Software Engineering · Computer Science 2016-05-10 Ogechi Onuoha

We generalise a fundamental graph-theoretical fact, stating that every element of the cycle space of a graph is a sum of edge-disjoint cycles, to arbitrary continua. To achieve this we replace graph cycles by topological circles, and…

General Topology · Mathematics 2011-10-28 Agelos Georgakopoulos

We introduce \emph{hierarchical depth}, a new invariant of line bundles and divisors, defined via maximal chains of effective sub-line bundles. This notion gives rise to \emph{hierarchical filtrations}, refining the structure of the Picard…

Algebraic Geometry · Mathematics 2025-10-29 Rahim Rahmati-asghar

We study spatially coupled LDPC codes that allow access to sub-blocks much smaller than the full code block. Sub-block access is realized by a semi-global decoder that decodes a chosen target sub-block by only accessing the target, plus a…

Information Theory · Computer Science 2020-10-22 Eshed Ram , Yuval Cassuto

We define multilevel codes on bipartite graphs that have properties analogous to multilevel serial concatenations. A decoding algorithm is described that corrects a proportion of errors equal to half the Blokh-Zyablov bound on the minimum…

Information Theory · Computer Science 2007-07-16 Alexander Barg , Gilles Zemor

We introduce group crosscoders, an extension of crosscoders that systematically discover and analyse symmetrical features in neural networks. While neural networks often develop equivariant representations without explicit architectural…

Machine Learning · Computer Science 2024-11-04 Liv Gorton