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Many machine learning methods look for low-dimensional representations of the data. The underlying subspace can be estimated by first choosing a dimension $q$ and then optimizing a certain objective function over the space of…

Machine Learning · Statistics 2025-12-19 Tom Szwagier , Xavier Pennec

This paper presents encoding and decoding algorithms for several families of optimal rank metric codes whose codes are in restricted forms of symmetric, alternating and Hermitian matrices. First, we show the evaluation encoding is the right…

Information Theory · Computer Science 2022-02-08 Wrya K. Kadir , Chunlei Li , Ferdinando Zullo

We develop a network coding technique based on flags of subspaces and a corresponding network channel model. To define error correcting codes we introduce a new distance on the flag variety, the Grassmann distance on flags and compare it to…

Information Theory · Computer Science 2016-12-22 Dirk Liebhold , Gabriele Nebe , Angeles Vazquez-Castro

Matrix multiplication (GEMM) is a core operation to numerous scientific applications. Traditional implementations of Strassen-like fast matrix multiplication (FMM) algorithms often do not perform well except for very large matrix sizes, due…

Mathematical Software · Computer Science 2016-11-04 Jianyu Huang , Leslie Rice , Devin A. Matthews , Robert A. van de Geijn

In this paper we study spread codes: a family of constant-dimension codes for random linear network coding. In other words, the codewords are full-rank matrices of size (k x n) with entries in a finite field F_q. Spread codes are a family…

Information Theory · Computer Science 2012-06-08 Elisa Gorla , Felice Manganiello , Joachim Rosenthal

Coding in the projective space has received recently a lot of attention due to its application in network coding. Reduced row echelon form of the linear subspaces and Ferrers diagram can play a key role for solving coding problems in the…

Information Theory · Computer Science 2009-03-14 Tuvi Etzion , Natalia Silberstein

In this paper, a lemma in algebraic coding theory is established, which is frequently appeared in the encoding and decoding for algebraic codes such as Reed-Solomon codes and algebraic geometry codes. This lemma states that two vector…

Information Theory · Computer Science 2012-08-28 Hajime Matsui

This paper introduces an online approach for identifying time-varying subspaces defined by linear dynamical systems. The approach of representing linear systems by non-parametric subspace models has received significant interest in the…

Systems and Control · Electrical Eng. & Systems 2025-12-01 András Sasfi , Alberto Padoan , Ivan Markovsky , Florian Dörfler

Let $V$ and $V'$ be vector spaces of dimension $n$ and $n'$, respectively. Let $k\in\{2,...,n-2\}$ and $k'\in\{2,...,n'-2\}$. We describe all isometric and $l$-rigid isometric embeddings of the Grassmann graph $\Gamma_{k}(V)$ in the…

Combinatorics · Mathematics 2011-09-27 Mark Pankov

The degree of the Grassmannian with respect to the Pl\"ucker embedding is well-known. However, the Pl\"ucker embedding, while ubiquitous in pure mathematics, is almost never used in applied mathematics. In applied mathematics, the…

Algebraic Geometry · Mathematics 2025-07-29 Lek-Heng Lim , Ke Ye

We propose a novel encoding scheme for algebraic codes such as codes on algebraic curves, multidimensional cyclic codes, and hyperbolic cascaded Reed-Solomon codes and present numerical examples. We employ the recurrence from the Gr\"obner…

Information Theory · Computer Science 2007-07-13 Hajime Matsui , Seiichi Mita

The problem of ranking can be described as follows. We have a set of combinatorial objects $S$, such as, say, the k-subsets of n things, and we can imagine that they have been arranged in some list, say lexicographically, and we want to…

Computational Complexity · Computer Science 2007-05-23 Boris Ryabko

We introduce the concepts of complex Grassmannian codes and designs. Let G(m,n) denote the set of m-dimensional subspaces of C^n: then a code is a finite subset of G(m,n) in which few distances occur, while a design is a finite subset of…

Combinatorics · Mathematics 2008-06-16 Aidan Roy

Graph neural networks (GNNs) are powerful tools on graph data. However, their predictions are mis-calibrated and lack interpretability, limiting their adoption in critical applications. To address this issue, we propose a new…

Machine Learning · Computer Science 2025-08-26 Lingkai Kong , Haotian Sun , Yuchen Zhuang , Haorui Wang , Wenhao Mu , Chao Zhang

Graphs have been extensively used to represent data from various domains. In the era of Big Data, information is being generated at a fast pace, and analyzing the same is a challenge. Various methods have been proposed to speed up the…

Information Theory · Computer Science 2018-06-26 Rushabh Jitendrakumar Shah

We propose a novel evolutionary algorithm for optimizing real-valued objective functions defined on the Grassmann manifold Gr}(k,n), the space of all k-dimensional linear subspaces of R^n. While existing optimization techniques on Gr}(k,n)…

Optimization and Control · Mathematics 2025-03-31 Andrew Lesniewski

Let $\mathbb{Z}_{p^s}$ be the residue class ring of integers modulo $p^s$, where $p$ is a prime number and $s$ is a positive integer. Using matrix representation and the inner rank of a matrix, we study the intersection, join, dimension…

Combinatorics · Mathematics 2017-05-15 Li-Ping Huang , Benjian Lv , Kaishun Wang

The Huffman coding algorithm is interpreted in the lattice of partitions of the source alphabet. Maximal chains in the partition lattice correspond to linear extensions of tree orders, and those among the chains that exhibit a simple greedy…

Combinatorics · Mathematics 2013-06-25 Stephan Foldes

The computational complexity of optimum decoding for an orthogonal space-time block code G satisfying the orthogonality property that the Hermitian transpose of G multiplied by G is equal to a constant c times the sum of the squared symbols…

Information Theory · Computer Science 2009-10-13 Ender Ayanoglu , Erik G. Larsson , Eleftherios Karipidis

Large scale numerical experiments are commonplace today in theoretical physics. The high performance algorithms described herein are the most compact, efficient methods known for representing and analyzing systems modeled well by sets or…

General Relativity and Quantum Cosmology · Physics 2018-05-14 William J. Cunningham