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Coded computing is a distributed paradigm that uses coding theory to introduce \textit{redundancy} and overcome bottlenecks in large-scale systems. In the same vein, randomized numerical linear algebra employs probabilistic methods to…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-19 Neophytos Charalambides , Arya Mazumdar

The motivation of this work stems from the numerical approximation of bounded functions by polynomials satisfying the same bounds. The present contribution makes use of the recent algebraic characterization found in [B. Despr\'es, Numer.…

Numerical Analysis · Mathematics 2020-06-30 Martin Campos Pinto , Frédérique Charles , Bruno Després , Maxime Herda

This thesis focuses on the intersection of mathematical and computational optimization and quantum information. Main contributions are open-source software code: A hybrid approach mixing "traditional" nonconvex and convex methods can make…

Quantum Physics · Physics 2025-12-19 Benjamin Desef

Through refined asymptotic analysis based on the normal approximation, we study how higher-order coding performance depends on the mean power as well as on finer statistics of the input power. We introduce a multifaceted power model in…

Information Theory · Computer Science 2026-05-13 Adeel Mahmood , Aaron B. Wagner

We recently showed in [1] the superiority of certain structured coding matrices ensembles (such as partial row-orthogonal) for sparse superposition codes when compared with purely random matrices with i.i.d. entries, both…

Information Theory · Computer Science 2022-07-12 YuHao Liu , Teng Fu , Jean Barbier , TianQi Hou

We use the implicitization procedure to generate polynomial equality constraints on the set of distributions induced by local interventions on variables governed by a causal Bayesian network with hidden variables. We show how we may reduce…

Artificial Intelligence · Computer Science 2012-06-26 Changsung Kang , Jin Tian

This paper addresses the problem of learning binary hash codes for large scale image search by proposing a novel hashing method based on deep neural network. The advantage of our deep model over previous deep model used in hashing is that…

Computer Vision and Pattern Recognition · Computer Science 2015-08-31 Thanh-Toan Do , Anh-Zung Doan , Ngai-Man Cheung

We present an extension of the Delsarte linear programming method. For several dimensions it yields improved upper bounds for kissing numbers and for spherical codes. Musin's recent work on kissing numbers in dimensions three and four can…

Combinatorics · Mathematics 2008-03-10 Florian Pfender

In the context of statistical learning, the Information Bottleneck method seeks a right balance between accuracy and generalization capability through a suitable tradeoff between compression complexity, measured by minimum description…

Information Theory · Computer Science 2021-02-16 Mohammad Mahdi Mahvari , Mari Kobayashi , Abdellatif Zaidi

This paper presents a program analysis method that generates program summaries involving polynomial arithmetic. Our approach builds on prior techniques that use solvable polynomial maps for summarizing loops. These techniques are able to…

Programming Languages · Computer Science 2023-12-08 John Cyphert , Zachary Kincaid

We consider a large-scale matrix multiplication problem where the computation is carried out using a distributed system with a master node and multiple worker nodes, where each worker can store parts of the input matrices. We propose a…

Information Theory · Computer Science 2018-01-25 Qian Yu , Mohammad Ali Maddah-Ali , A. Salman Avestimehr

We develop a new tool, namely polynomial and linear algebraic methods, for studying systems of word equations. We illustrate its usefulness by giving essentially simpler proofs of several hard problems. At the same time we prove extensions…

Combinatorics · Mathematics 2015-02-10 Aleksi Saarela

The unit-derived method in coding theory is shown to be a unique optimal scheme for constructing and analysing codes. In many cases efficient and practical decoding methods are produced. Codes with efficient decoding algorithms at maximal…

Information Theory · Computer Science 2020-04-14 Ted Hurley , Donny Hurley

An additive noise channel is considered, in which the distribution of the noise is nonparametric and unknown. The problem of learning encoders and decoders based on noise samples is considered. For uncoded communication systems, the problem…

Information Theory · Computer Science 2021-11-17 Nir Weinberger

In this article we present a unified treatment for obtaining bounds on the potential energy of codes in the general context of polynomial metric spaces (PM-spaces). The lower bounds we derive via the linear programming (LP) techniques of…

Metric Geometry · Mathematics 2018-04-23 Peter Boyvalenkov , Peter Dragnev , Douglas Hardin , Edward Saff , Maya Stoyanova

Proving capacity for networks without feedback or cooperation usually involves two fundamental random coding techniques: superposition coding and binning. Although conceptually very different, these two techniques often achieve the same…

Information Theory · Computer Science 2012-02-08 Stefano Rini

Even when neural networks are widely used in a large number of applications, they are still considered as black boxes and present some difficulties for dimensioning or evaluating their prediction error. This has led to an increasing…

Machine Learning · Statistics 2021-05-11 Pablo Morala , Jenny Alexandra Cifuentes , Rosa E. Lillo , Iñaki Ucar

We study the theoretical performance of a combined approach to demodulation and decoding of binary continuous-phase modulated signals under repetition-like codes. This technique is motivated by a need to transmit packetized or framed data…

Information Theory · Computer Science 2014-04-28 Gaurav Thakur

We consider bounds on codes in spherical caps and related problems in geometry and coding theory. An extension of the Delsarte method is presented that relates upper bounds on the size of spherical codes to upper bounds on codes in caps.…

Metric Geometry · Mathematics 2007-07-16 Alexander Barg , Oleg R. Musin

In this work, we present an abstract framework for some algebraic error-correcting codes with the aim of capturing codes that are list-decodable to capacity, along with their decoding algorithm. In the polynomial ideal framework, a code is…

Information Theory · Computer Science 2023-12-21 Siddharth Bhandari , Prahladh Harsha , Mrinal Kumar , Madhu Sudan