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We introduce a novel type of approximation spaces for functions with values in a nonlinear manifold. The discrete functions are constructed by piecewise polynomial interpolation in a Euclidean embedding space, and then projecting pointwise…

Numerical Analysis · Mathematics 2018-03-20 Philipp Grohs , Hanne Hardering , Oliver Sander , Markus Sprecher

We design the first efficient algorithms and prove new combinatorial bounds for list decoding tensor products of codes and interleaved codes. We show that for {\em every} code, the ratio of its list decoding radius to its minimum distance…

Information Theory · Computer Science 2008-11-27 Parikshit Gopalan , Venkatesan Guruswami , Prasad Raghavendra

Recently, versions of neural networks with infinite-dimensional affine operators inside the computational units (``neural operator'' networks) have been applied to learn solutions to differential equations. To enable practical computations,…

Functional Analysis · Mathematics 2026-02-03 Vinícius Luz Oliveira , Vladimir G. Pestov

We establish Maximum Principles which apply to vectorial approximate minimizers of the general integral functional of Calculus of Variations. Our main result is a version of the Convex Hull Property. The primary advance compared to results…

Analysis of PDEs · Mathematics 2013-04-22 Nikolaos I. Katzourakis

We derive upper bounds on the difference between the orthogonal projections of a smooth function $u$ onto two finite element spaces that are nearby, in the sense that the support of every shape function belonging to one but not both of the…

Numerical Analysis · Mathematics 2014-08-19 Evan S. Gawlik , Adrian J. Lew

Sequence classification has numerous applications in various fields. Despite extensive studies in the last decades, many challenges still exist, particularly in pattern-based methods. Existing pattern-based methods measure the…

Machine Learning · Computer Science 2023-10-23 Junjie Dong , Mudi Jiang , Lianyu Hu , Zengyou He

Higher-order Fourier analysis, developed over prime fields, has been recently used in different areas of computer science, including list decoding, algorithmic decomposition and testing. We extend the tools of higher-order Fourier analysis…

Data Structures and Algorithms · Computer Science 2015-05-05 Arnab Bhattacharyya , Abhishek Bhowmick

In this paper, we examine the hash functions expressed as scalar products, i.e., $f(x)=<v,x>$, for some bounded random vector $v$. Such hash functions have numerous applications, but often there is a need to optimize the choice of the…

Data Structures and Algorithms · Computer Science 2017-04-21 Piotr Wygocki

Feature hashing, also known as {\em the hashing trick}, introduced by Weinberger et al. (2009), is one of the key techniques used in scaling-up machine learning algorithms. Loosely speaking, feature hashing uses a random sparse projection…

Machine Learning · Computer Science 2018-05-23 Casper Benjamin Freksen , Lior Kamma , Kasper Green Larsen

Recently, codes in the sum-rank metric attracted attention due to several applications in e.g. multishot network coding, distributed storage and quantum-resistant cryptography. The sum-rank analogs of Reed-Solomon and Gabidulin codes are…

Information Theory · Computer Science 2022-09-07 Felicitas Hörmann , Hannes Bartz

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

Let $q$ be an odd prime power and let $X(m,q)$ be the set of symmetric bilinear forms on an $m$-dimensional vector space over $\mathbb{F}_q$. The partition of $X(m,q)$ induced by the action of the general linear group gives rise to a…

Combinatorics · Mathematics 2014-10-28 Kai-Uwe Schmidt

Sum-rank Hamming codes are introduced in this work. They are essentially defined as the longest codes (thus of highest information rate) with minimum sum-rank distance at least $ 3 $ (thus one-error-correcting) for a fixed redundancy $ r $,…

Information Theory · Computer Science 2021-01-13 Umberto Martínez-Peñas

We provide sufficient conditions for quantitative convergence of the iterates of proximal splitting algorithms for minimizing a sum of functions on a metric space. The theory does not assume that the functions have common minima, nor does…

Optimization and Control · Mathematics 2026-05-06 D. Russell Luke , Mahshid Mirhashemi

An ordinary differential field $(F,d)$ of characteristic zero, a subgroup $H$ of affine group $ GL(n,C)\propto C^n$ with respect to its identical representation in $F^n$ and the following two fields of differential rational functions in…

Algebraic Geometry · Mathematics 2007-05-23 Ural Bekbaev

In this letter we consider the ensemble of codes formed by the serial concatenation of a Hamming code and two accumulate codes. We show that this ensemble is asymptotically good, in the sense that most codes in the ensemble have minimum…

Information Theory · Computer Science 2009-05-29 Alexandre Graell i Amat , Raphael Le Bidan

For a nonempty convex subset $C$ of a Hadamard space $X$, it is proved that $u=P_Cx$ if and only if $\langle\overrightarrow{xu},\overrightarrow{uy}\rangle \geqslant0$ for all $y\in C$. As an application of this characterization, we prove…

Functional Analysis · Mathematics 2014-10-07 Hossein Dehghan , Jamal Rooin

Let $\{S_i\}_{i=1}^\ell$ be an iterated function system (IFS) on $\R^d$ with attractor $K$. Let $(\Sigma,\sigma)$ denote the one-sided full shift over the alphabet $\{1,..., \ell\}$. We define the projection entropy function $h_\pi$ on the…

Dynamical Systems · Mathematics 2010-02-11 De-Jun Feng , Huyi Hu

In this paper, we study the angle testing problem in the context of similarity search in high-dimensional Euclidean spaces and propose two projection-based probabilistic kernel functions, one designed for angle comparison and the other for…

Machine Learning · Computer Science 2026-03-03 Kejing Lu , Chuan Xiao , Yoshiharu Ishikawa

In this work, we consider a class of convex optimization problems in a real Hilbert space that can be solved by performing a single projection, i.e., by projecting an infeasible point onto the feasible set. Our results improve those…

Optimization and Control · Mathematics 2024-04-10 Hoa T. Bui , Regina S. Burachik , Evgeni A. Nurminski , Matthew K. Tam