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We consider a variant of the clustering problem for a complete weighted graph. The aim is to partition the nodes into clusters maximizing the sum of the edge weights within the clusters. This problem is known as the clique partitioning…

Social and Information Networks · Computer Science 2023-09-15 Alexander Belyi , Stanislav Sobolevsky , Alexander Kurbatski , Carlo Ratti

This paper studies the performance of block coding on an additive white Gaussian noise channel under different power limitations at the transmitter. Lower bounds are presented for the minimum error probability of codes satisfying maximal…

Information Theory · Computer Science 2020-08-19 Gonzalo Vazquez-Vilar

It is common practice to collect observations of feature and response pairs from different environments. A natural question is how to identify features that have consistent prediction power across environments. The invariant causal…

Information Theory · Computer Science 2022-07-01 Austin Goddard , Yu Xiang , Ilya Soloveychik

We propose a linear programming (LP) framework for steady-state diffusion and flux optimization on geometric networks. The state variable satisfies a discrete diffusion law on a weighted, oriented graph, where conductances are scaled by…

Optimization and Control · Mathematics 2025-11-06 Harbir Antil , Rainald Löhner , Felipe Pérez

We consider $t$-Lee-error-correcting codes of length $n$ over the residue ring $\mathbb{Z}_m := \mathbb{Z}/m\mathbb{Z}$ and determine upper and lower bounds on the number of $t$-Lee-error-correcting codes. We use two different methods,…

Information Theory · Computer Science 2023-05-11 Nadja Willenborg , Anna-Lena Horlemann , Violetta Weger

Determining the number of embeddings of Laman graph frameworks is an open problem which corresponds to understanding the solutions of the resulting systems of equations. In this paper we investigate the bounds which can be obtained from the…

Combinatorics · Mathematics 2009-03-13 Reinhard Steffens , Thorsten Theobald

A fundamental tool in network information theory is the covering lemma, which lower bounds the probability that there exists a pair of random variables, among a give number of independently generated candidates, falling within a given set.…

Information Theory · Computer Science 2019-04-18 Jingbo Liu , Mohammad H. Yassaee , Sergio Verdú

Just as the Hamming weight spectrum of a linear block code sheds light on the performance of a maximum likelihood decoder, the pseudo-weight spectrum provides insight into the performance of a linear programming decoder. Using properties of…

Information Theory · Computer Science 2016-11-17 Panu Chaichanavong , Paul H. Siegel

One of the main problems in random network coding is to compute good lower and upper bounds on the achievable cardinality of the so-called subspace codes in the projective space $\mathcal{P}_q(n)$ for a given minimum distance. The…

Information Theory · Computer Science 2020-11-16 Tao Feng , Sascha Kurz , Shuangqing Liu

We explore the relation between the techniques of statistical mechanics and information theory for assessing the performance of channel coding. We base our study on a framework developed by Gallager in {\em IEEE Trans. Inform. Theory} {\bf…

Information Theory · Computer Science 2009-11-13 Yoshiyuki Kabashima

When performing maximum-likelihood quantum-state tomography, one must find the quantum state that maximizes the likelihood of the state given observed measurements on identically prepared systems. The optimization is usually performed with…

Quantum Physics · Physics 2012-10-26 Scott Glancy , Emanuel Knill , Mark Girard

We develop a new family of linear programs, that yield upper bounds on the rate of binary linear codes of a given distance. Our bounds apply {\em only to linear codes.} Delsarte's LP is the weakest member of this family and our LP yields…

Information Theory · Computer Science 2022-11-16 Elyassaf Loyfer , Nati Linial

In this paper we consider a Metzner-Kapturowski-like decoding algorithm for high-order interleaved sum-rank-metric codes, offering a novel perspective on the decoding process through the concept of an error code. The error code, defined as…

Information Theory · Computer Science 2024-09-30 Thomas Jerkovits , Felicitas Hörmann , Hannes Bartz

This paper develops upper and lower bounds for the probability of Boolean expressions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. Our technique generalizes and extends the…

Artificial Intelligence · Computer Science 2015-03-19 Wolfgang Gatterbauer , Dan Suciu

Maximum Likelihood (ML) decoding of forward error correction codes is known to be optimally accurate, but is not used in practice as it proves too challenging to efficiently implement. Here we introduce a ML decoder called SGRAND, which is…

Information Theory · Computer Science 2020-01-10 Amit Solomon , Ken R. Duffy , Muriel Médard

Multiplication is one of the most fundamental computational problems, yet its true complexity remains elusive. The best known upper bound, by F\"{u}rer, shows that two $n$-bit numbers can be multiplied via a boolean circuit of size $O(n \lg…

Data Structures and Algorithms · Computer Science 2019-03-01 Peyman Afshani , Casper Benjamin Freksen , Lior Kamma , Kasper Green Larsen

In this paper, we study ultra-reliable and low-latency communication (URLLC) under fading using multiple frequency or time bins. We investigate an approach to find an upper-bound on the packet error rate when a finite-length code is used.…

Information Theory · Computer Science 2019-04-08 Jinho Choi

Error correction codes are a crucial part of the physical communication layer, ensuring the reliable transfer of data over noisy channels. The design of optimal linear block codes capable of being efficiently decoded is of major concern,…

Information Theory · Computer Science 2024-05-08 Yoni Choukroun , Lior Wolf

The classic lower bound of Kuhn, Moscibroda and Wattenhofer [JACM 2016] states that approximate maximum matching and approximate vertex cover (among other problems) in the LOCAL model require $\Omega(\min\{\sqrt{\frac{\log n}{\log\log n}},…

Data Structures and Algorithms · Computer Science 2026-05-14 Peter Davies-Peck

In this paper we carefully study the MSE performance of the linear analog codes. We have derived a lower bound of the MSE performance under Likelihood(ML) and Linear Minimal Mean Square Error(LMMSE) decoding criteria respectively. It is…

Information Theory · Computer Science 2015-11-19 Yang Liu , Jing Li , Kai Xie