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We consider the problem of describing the typical (possibly) non-linear code of minimum distance bounded from below over a large alphabet. We concentrate on block codes with the Hamming metric and on subspace codes with the injection…

Information Theory · Computer Science 2021-11-24 Anina Gruica , Alberto Ravagnani

To improve performance in contemporary deep learning, one is interested in scaling up the neural network in terms of both the number and the size of the layers. When ramping up the width of a single layer, graceful scaling of training has…

Machine Learning · Computer Science 2024-05-24 Tim Large , Yang Liu , Minyoung Huh , Hyojin Bahng , Phillip Isola , Jeremy Bernstein

Kulkarni and Kiyavash recently introduced a new method to establish upper bounds on the size of deletion-correcting codes. This method is based upon tools from hypergraph theory. The deletion channel is represented by a hypergraph whose…

Information Theory · Computer Science 2014-01-28 Arman Fazeli , Alexander Vardy , Eitan Yaakobi

The index coding problem involves a sender with K messages to be transmitted across a broadcast channel, and a set of receivers each of which demands a subset of the K messages while having prior knowledge of a different subset as side…

Information Theory · Computer Science 2016-11-17 Lakshmi Natarajan , Yi Hong , Emanuele Viterbo

A coding scheme with scalar lattices is applied to K-receiver, Gaussian, vector broadcast channels with K independent messages, one for each receiver. The method decomposes each receiver channel into parallel scalar channels with known…

Information Theory · Computer Science 2024-04-25 M. Yusuf Şener , Gerhard Kramer , Shlomo Shamai , Ronald Böhnke , Wen Xu

The sum-rank metric naturally extends both the Hamming and rank metrics in coding theory over fields. It measures the error-correcting capability of codes in multishot matrix-multiplicative channels (e.g. linear network coding or the…

Information Theory · Computer Science 2019-01-31 Umberto Martínez-Peñas

Consider a pair of correlated Gaussian sources (X1,X2). Two separate encoders observe the two components and communicate compressed versions of their observations to a common decoder. The decoder is interested in reconstructing a linear…

Information Theory · Computer Science 2007-07-25 D. Krithivasan , S. S. Pradhan

A new class of folded subspace codes for noncoherent network coding is presented. The codes can correct insertions and deletions beyond the unique decoding radius for any code rate $R\in[0,1]$. An efficient interpolation-based decoding…

Information Theory · Computer Science 2015-04-22 Hannes Bartz , Vladimir Sidorenko

We prove the following results regarding the linear solvability of networks over various alphabets. For any network, the following are equivalent: (i) vector linear solvability over some finite field, (ii) scalar linear solvability over…

Information Theory · Computer Science 2018-01-31 Joseph Connelly , Kenneth Zeger

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

We consider analog error-correcting codes (analog ECCs) that are designed to correct/detect outlying errors arising in analog implementations of vector-matrix multiplication. The error-correction/detection capability of an analog ECC can be…

Information Theory · Computer Science 2026-04-07 Wentu Song , Kui Cai

A lower bound on the number of uncorrectable errors of weight half the minimum distance is derived for binary linear codes satisfying some condition. The condition is satisfied by some primitive BCH codes, extended primitive BCH codes,…

Information Theory · Computer Science 2008-04-30 Kenji Yasunaga , Toru Fujiwara

In recent work, it has been shown that maintaining reliability in analog vector--matrix multipliers can be modeled as the following coding problem. Vectors in $\mathbb{R}^k$ are encoded into codewords of a linear $[n,k,d]$ code $C$ over…

Information Theory · Computer Science 2026-02-25 Ron M. Roth , Ziyuan Zhu , Changcheng Yuan , Paul H. Siegel , Anxiao Jiang

Largest theoretical contribution to Neural Networks comes from VC Dimension which characterizes the sample complexity of classification model in a probabilistic view and are widely used to study the generalization error. So far in the…

Machine Learning · Computer Science 2024-09-05 Linu Pinto , Sasi Gopalan

A modification of Koetter-Kschischang codes for random networks is presented (these codes were also studied by Wang et al. in the context of authentication problems). The new codes have higher information rate, while maintaining the same…

Information Theory · Computer Science 2016-11-17 Vitaly Skachek

Following the approach by R. K\"otter and F. R. Kschischang, we study network codes as families of k-dimensional linear subspaces of a vector space F_q^n, q being a prime power and F_q the finite field with q elements. In particular,…

Information Theory · Computer Science 2013-06-25 Elisa Gorla , Alberto Ravagnani

Network coding is studied when an adversary controls a subset of nodes in the network of limited quantity but unknown location. This problem is shown to be more difficult than when the adversary controls a given number of edges in the…

Information Theory · Computer Science 2011-12-15 Oliver Kosut , Lang Tong , David Tse

Permutation codes, in the form of rank modulation, have shown promise for applications such as flash memory. One of the metrics recently suggested as appropriate for rank modulation is the Ulam metric, which measures the minimum…

Information Theory · Computer Science 2017-01-17 Justin Kong , Manabu Hagiwara

In the practical network communications, many internal nodes in the network are required to not only transmit messages but decode source messages. For different applications, four important classes of linear network codes in network coding…

Information Theory · Computer Science 2013-12-02 Xuan Guang , Fang-Wei Fu

A new lower bound on the average reconstruction error variance of multidimensional sampling and reconstruction is presented. It applies to sampling on arbitrary lattices in arbitrary dimensions, assuming a stochastic process with constant,…

Information Theory · Computer Science 2018-06-19 Erik Agrell , Balázs Csébfalvi